@article{ author = {Seyyedsalehi, Seyyede Zohreh and Seyyedsalehi, Seyyed Ali}, title = {Improving the nonlinear manifold separator model to the face recognition by a single image of per person}, abstract ={Manifold learning is a dimension reduction method for extracting nonlinear structures of high-dimensional data. Many methods have been introduced for this purpose. Most of these methods usually extract a global manifold for data. However, in many real-world problems, there is not only one global manifold, but also additional information about the objects is shared by a large number of manifolds. In this context, based on previous researches, this paper proposes a nonlinear dimension reduction method based on the deep neural network that extract simultaneously manifolds embedded in data. In nonlinear manifold separator model, unlike unsupervised learning of bottleneck neural network, data labels are indirectly used for manifold learning. Given the deep structure of the model, it has been shown that using pre-training methods can significantly improve its performance moreover, to improve within-manifold discrimination for different classes, its standard functions have been improved. This paper makes use of the model for extracting both expression and identity manifolds for facial images of the CK+ database. In comparing early and improved models, it is shown that the facial expression recognition rate from 24.29% to 75.07% and the face recognition rate by a single image of each person by enriching dataset from 90.62% to 97.07% were improved.}, Keywords = {Neural network • Manifold learning • Within-manifold discrimination • Virtual patterns • Deep structure • Manifold separation}, volume = {12}, Number = {1}, pages = {3-16}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-181-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-181-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Asgharian, Hassan and taj, nasri}, title = {IMS SIP Server security model using the TVRA methodology}, abstract ={IMS (IP Multimedia Subsystem) network is considered as an NGN (Next Generation Network) core networks by ETSI. Decomposition of IMS core network has resulted in a rapid increase of control and signaling message that makes security a required capability for IMS commercialization. The control messages are transmitted using SIP (Session Initiation Protocol) which is an application layer protocol. IMS networks are more secure than typical networks like VoIP according to mandatory of user authentication in registration time and added SIP signaling headers. Also different vulnerabilities have been occurred that lead to SIP servers attacks. This paper studies the main SIP servers of IMS (x-CSCF) based on ETSI Threat, Vulnerability and Risk Analysis (TVRA) method. This method is used as a tool to identify potential risks to a system based upon the likelihood of an attack and the impact that such an attack would have on the system. After identifying the assets and weaknesses of IMS SIP servers and finding out the vulnerabilities of these hardware and software components, some security hints that can be used for secure deployment of IMS SIP servers are proposed. Modeling shows the effects of server weaknesses and threats that reduces availability. Any designed system has some assets with weaknesses. When threats have accrued based on weaknesses, the system will vulnerable. Vulnerability analysis optimizes costs and improves security.}, Keywords = {TVRA Security Modeling, IMS SIP Servers Flooding attacks, IMS architecture and network Vulnerability assessment.}, volume = {12}, Number = {1}, pages = {17-32}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-64-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-64-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Pourghassem, Hossei}, title = {A Feature-based Vehicle Tracking Algorithm Using Merge and Split-based Hierarchical Grouping}, abstract ={Vehicle tracking is an important issue in Intelligence Transportation Systems (ITS) to estimate the location of vehicle in the next frame. In this paper, a feature-based vehicle tracking algorithm using Kanade-Lucas-Tomasi (KLT) feature tracker is developed. In this algorithm, a merge and split-based hierarchical two-stage grouping algorithm is proposed to represent vehicles from the tracked features. In the proposed grouping algorithm, with defining measures such as distance, spread and also blob analysis, initial grouping results formed by K-means clustering algorithm are refined. Moreover, to modify the performance of KLT tracker and also optimized utilization from grouping results obtained by proposed algorithm, an effective group matching algorithm based on a merging and splitting scheme is employed to match the tracked groups from a frame to the next frame. The proposed tracking algorithm is evaluated on different test videos with various illumination conditions such as day, night and shadow. The obtained results show that our proposed tracking algorithm covers the most challenges of tracking in the ITS applications.}, Keywords = {Merge and split hierarchical two-stage grouping algorithm, Group matching algorithm based on merge and split schemes, Feature-based tracking algorithm, Intelligence transportation system.}, volume = {12}, Number = {1}, pages = {33-46}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-165-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-165-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Montazer, Gholam Ali and shayestehfar, mohamm}, title = {Iranian License Plate identification with fuzzy support vector machine}, abstract ={License plate recognition is one of the most important applications used in intelligent transportation systems. Difficulty of correct detection and identification of the car plates in different environment conditions makes researchers try new approaches to better solve the problem. License plate recognition problem is divided into three sub problems: "Plate Location", "Character Segmentation", and "Character Identification". In this paper we have tried to improve location and identification of Iranian license plate with fuzzy rules. License locating has been done with edge detection, morphological operations and using fuzzy rules and characters have been identified by fuzzy support vector machine. By applying the algorithm on 50 images, 90% of plates were located and 94% of characters were identified successfully. This shows superiority of our algorithm over non-fuzzy approaches.}, Keywords = {fuzzy theory, license plate, pattern recognition, support vector machine (FSVM) }, volume = {12}, Number = {1}, pages = {47-56}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-120-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-120-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Farsi, Hassan and Etezadifar, Pouri}, title = {Robustness of Motion Vector against Channel Error for Improvement of Synthesized Video Quality}, abstract ={According to progress of technology during the recent decades, video transmission through a wireless channel has found high demands. In this field, several methods have been proposed to improve video quality. Appearing error in motion vector values is one of the most important factors which can affect the video quality. In case of creating errors in motion vector, the synthesized video frames are moved compared to the previous situation and therefore the synthesized video quality considerably degrades. In this paper, in order to overcome this problem and also to increase PSNR, we propose a method to increase the channel coding rate but transmission rate is maintained constant. In the proposed method, firstly, the motion vector is searched in each block with size of 8*8. After ending the search, the adjacent blocks with the motion vector equals to zero (without movement) are combined together and provide bigger block. Meanwhile, the blocks with equal motion vectors are combined together and transmitted to receiver in two different methods. The experimental results show that the proposed method without increasing side information is able to provide more robustness for video frame against channel errors. The performance of the proposed method has been compared with the new method for different source coding rates and SNRs.}, Keywords = {: Motion vector, Video frame coding, Variable bit rate, Channel coding }, volume = {12}, Number = {1}, pages = {57-78}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-43-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-43-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Geravanchizadeh, Masoud and Fallah, Ali and Eterafoskouei, Mirali}, title = {Prediction of consonants Intelligibility for Listeners with Normal Hearing Using Microscopic Models of Speech Perception Considering Different Distance Measures in Automatic Speech Recognizer}, abstract ={In this study, recognition rates of consonants available in vowel-consonant-vowel structure in hearing tests and two microscopic models will be investigated. Such a syllable structure doesn’t exist in Farsi and Azerbaijani languages, but since the goal is only recognition of middle phoneme, according to hearing tests, listeners are able to properly recognize phonemes in clean speech conditions. Inasmuch as these syllable structures are meaningless, it will be suitable for our purpose that is only determination of recognition rates of phonemes not meaningful words. Using this corpus, listeners’ linguistic knowledge in prediction of words is disregarded. Results of hearing tests are compared with two microscopic models based on human auditory system. Difference between two models is at the final stage of feature extraction that in first model, a 8 Hz filter and in the second model a modulation filterbank is used. Correct recognition rates of phonemes in different signal to noise ratios and two distance metrics for speech recognizer, will be compared. In this study recognition rates of consonants for listeners with Azerbaijani native language have been studied. Beside the empirical aspect of the paper, the innovations of this work lies in the study of using two different distance measures for Holube’s model and also direct comparison of two microscopic models in prediction of overall recognition rates and recognition rate of each consonant.}, Keywords = {Intelligibility, Speech perception, Microscopic model, Feature vector, Phoneme recognition rate, Distance measure, Automatic Speech Recognizer. }, volume = {12}, Number = {1}, pages = {79-90}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-180-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-180-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Tabatabaei, Raziyeh and Feizi-Derakhshi, Mohammad-Reza and Masoumi, Saei}, title = {Proposing an intelligent and semantic-based system for Evaluating Text Summarizers}, abstract ={Nowadays summarizers and machine translators have attracted much attention to themselves, and many activities on making such tools have been done around the world. For Farsi like the other languages there have been efforts in this field. So evaluating such tools has a great importance. Human evaluations of machine summarization are extensive but expensive. Human evaluations can take months to finish and involve human labor that cannot be reused. In this paper, we propose a method of automatic machine summarization evaluation that is quick, inexpensive, and language-independent, that correlates highly with human evaluation, and that has little marginal cost per run. This method has the metrics of determining auto summaries’ quality, through comparing them to the summaries produced by Human (ideal summaries). These metrics measures overlapping of system summaries and human ones in number of units like n-tuples, words string and pairs of words. Certainly for semantic comparing of texts in case of review summaries, the appearance of words are not enough and using of WordNet seems to be necessary. In the proposed method words network is used with an appropriate idea and has improved evaluation results significantly. The proposed method is the first method for the Persian language. Performance measurement of the tool was done during a specified and standard procedure and the results indicate acceptable yield of it. We present this method as an automated understudy to skilled human judges which substitutes for them when there is need for quick or frequent evaluations.}, Keywords = {Natural Language Processing, Persian Language, System Summarizer Evaluation, Evaluation measure.}, volume = {12}, Number = {2}, pages = {3-11}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-182-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-182-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {khodadadi, habib and rahatiquchani, saeed and estaji, azam}, title = {Contrast Relation Recognition in Persian discourse using supervised learning methods}, abstract ={Discourse is a part of language that intend is used to communicate. A discourse relation recognition system can identify one or more relation between the textual units in a discourse. Like other languages, Contrast relation is a one of the available relations in Persian discourse. Contrast relation recognition in discourse is useful for generation and perception of discourse, paraphrasing and summarization systems and et al. This relation in one discourse is often detected by discourse marker such as “اما” and “ولی”, But in some situation these markers are removed and relation recognition is difficult. For this reason we have proposed to use of some feature for relation recognition. These features are: tense of verbs, word pairs, and et al. In this paper, a Corpus of Research Center of Intelligent Signal Processing has been used to collect 5000 instances of contrast and 5000 other relations then created feature vector for each instance. We used three supervised methods for classification: SVM, KNN ,Parzen Window and combine of this classifiers. Finally, the best result achieved by combine classifier that accuracy is 87.13.}, Keywords = {Contrast Relation Recognition , Discourse, Discourse Marker, Natural Language Processing, Supervised Learning}, volume = {12}, Number = {2}, pages = {13-22}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-45-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-45-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {hoseinkhani, fatemeh and nasersharif, babak}, title = {Two Featuer Transformation Methods Based on Genetic Algorithm for Reducing Support Vector Machine Classification Error}, abstract ={Discriminative methods are used for increasing pattern recognition and classification accuracy. These methods can be used as discriminant transformations applied to features or they can be used as discriminative learning algorithms for the classifiers. Usually, discriminative transformations criteria are different from the criteria of  discriminant classifiers training or  their error. In this paper, for relating feature transformation criterion to classification rate, we obtain a feature transformation method using genetic algorithm where we choose fitness function as Support Vectomr Machine(SVM) classification error rate. In addition, we obtain a feature transformation method using multi-objective genetic algorithm in order to consider both between class discrimination (According to feature transformation criterion) and support vector machine classification error rate simultaneously. Experimental results on UCI dataset indicate that using both classification error and between class discrimination in feature transformation improve discriminative feature transformations performance in increasing SVM classification accuracy. Additionally, the use of feature transformation with classification error criterion increases SVM classification more than other conventional feature transformation and proposed two-objective methods.}, Keywords = {Feature Transformation, Discrimination, Support Vector Machine, Genetic Algorithms, Classification.}, volume = {12}, Number = {2}, pages = {23-39}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-185-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-185-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Hasanzadeh, Fatemeh and Shahabi, Hossein and Moghimi, Sahar and Moghimi, Ali}, title = {EEG investigation of the effective brain networks for recognizing musical emotions}, abstract ={In the current research brain effective networks related to happy and sad emotions are studied during listening to music. Connectivity patterns among different EEG channels were extracted using multivariate autoregressive modeling and partial directed coherence while participants listened to musical excerpts. Both classical and Iranian musical selections were used as stimulus. Participants’ self-reported emotional values were used for classification of excerpts. The connectivity matrices varied from happy to sad musical selections. Moreover, the parameters extracted from different regions correlated with subjective assessments of the emotional content. Self-reported valance had a positive correlation with the inflow of frontal channels while listening to happy excerpts. This correlation was negative for sad pieces. The obtained results demonstrate that the connectivity indices among different regions can be used for differentiating happy and sad emotions.}, Keywords = {EEG, emotion, music, partial directed coherence, effective network}, volume = {12}, Number = {2}, pages = {41-54}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-198-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-198-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {rahimi, zeinab and samani, mohammad hossein and khadivi, shahram}, title = {Extracting parallel corpora from web comparable documents to improve the quality of an English-Farsi translation system}, abstract ={Data used for training statistical machine translation method are usually prepared from three resources: parallel, non-parallel and comparable text corpora. Parallel corpora are an ideal resource for translation but due to lack of these kinds of texts, non-parallel and comparable corpora are used either for parallel text extraction. Most of existing methods for exploiting comparable corpora look for parallel data at the sentence level. However, we believe that very non-parallel corpora have none or few good sentence pairs most of their parallel data exists at the sub-sentential level. The base system is Manteanu 2006 fragment extraction system implemented in C# and the proposed system is implemented based on extracting fragment blocks from input related sentences using score calculated from special features such as fragment length, LLR score, relevance path specification in the block and translation coverage percent. Evaluations indicates that proposed method outperforms the base system and the improved base system.}, Keywords = {Comparable Corpora, Fragment Extraction, Parallel Corpora, Machine Translation}, volume = {12}, Number = {2}, pages = {55-72}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-190-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-190-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Ghodousi, mahrad and Nasrabadi, Ali moti and Torabi, Shahla and Mohammadian, Amin and Mehrnam, AmirHossei}, title = {Combination of event related potentials and Peripheral signals in order to improve the accuracy of the Lie detection Systems}, abstract ={Since it was being predicted that combination of psychophysiological and ERP signals, during the detection of a guilty person's knowledge can increase the performance of integrative lie detection system toward using the separate procedures Using the knowledge of both aspects, in this study it has been tried to determine the proper Inter-Stimulus Intervals (ISI) together with suitable sequence of stimulations in order to simultaneous recording of P300 component of brain Event Related Potentials and peripheral signals. Also a proper mock crime scenario has been designed it has the capability of exciting the cognitive aspect of mock crime and also was capable of provoking the subject’s concerns, based on telling lie about the crime. At the next stage, after recording data from 32 participants, features from their ERP and SCR (as one of the most important peripheral signals) signals have been extracted. Then, an LDA classifier was applied on selected features which were selected by Genetic algorithm and these accuracies: 76.67%, 73.33% & 80% have been obtained for EEG, SCR and Combined data respectively. The resulted accuracies at the first show the proper quality of scenario and protocol, in synchronous stimulation and recording of both signal categories, also the improvements which have been resulted by integrative data in compare with separate ones are observable.}, Keywords = {Oddball paradigm, Event Related Potentials, Integrated Lie-detection analysis, Peripheral Signals}, volume = {12}, Number = {2}, pages = {73-86}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-36-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-36-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {}, title = {Extractive summarization based on cognitive aspects of human mind for narrative text}, abstract ={This study explains a summarization system based on a cognitive model theory. This theory is about comprehension and is used to explain comprehending narrative texts. Majority of previous methods have been used statistical approaches for summarization, and this method is different as it tries to build a system based on a cognitive theory and not statistical methods. Main principle of situational model is that as humans read a text, they will make a mental image based on temporality, causality, intentionality, protagonists, and place. Proposed system extracts five features for each sentence and identifies the most important sentences based on five features. The results obtained from this method were satisfactory.}, Keywords = {Extractive summarization, Situational model theory, Cognitive Science, Narrative text}, volume = {12}, Number = {2}, pages = {87-96}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-203-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-203-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {}, title = {Speech Enhancement Using MMSE Estimator Based on Mixture of laplacian}, abstract ={In this paper an estimator of speech spectrum for speech enhancement based on Laplacian Mixture Model has been proposed. We present an analytical solution for estimating the complex DFT coefficients with the MMSE estimator when the clean speech DFT coefficients are mixture of Laplacians distributed. The distribution of the DFT coefficients of noise are assumed zero-mean Gaussian.The drived MMSE estimator is non-linear and it was shown that this estimator performs better than estimators which are based on Gaussian and Laplacin model}, Keywords = {EM algorithm, Gaussian noise, Laplacian Mixture Model, Minimum Statistic,MMSE estimator. }, volume = {12}, Number = {2}, pages = {97-107}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-54-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-54-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Mirzababaei, Behzad and Faili, Heshaam}, title = {A real-world spell checker using context-sensitive features}, abstract ={Nowadays, a large volume of documents is generated daily. These documents generated by different persons, thus, the documents contain spelling errors. These spelling errors cause quality of the documents are decrease. Therefore, existence of automatic writing assistance tools such as spell checker/corrector can help to improve their quality. Context-sensitive are misspelled words that have been wrongly converted into another word of the language. Thus, detection of real-word errors requires discourse analysis. In this paper, we propose a language independent discourse-aware discriminative ranker and use information of whole document and a log-linear model for ranking. To evaluate our method, we augment it into two context-sensitive spellchecker systems one is based on Statistical Machine Translation (SMT) and the other is based on language model. For more evaluation, we also use two different tests. Proposed method cause outperform about 17% over the SMT base approach with respect to detection and correction recall.}, Keywords = {Spell checker, context-sensitive error, statistical machine translation, context-aware ranking}, volume = {12}, Number = {3}, pages = {3-14}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-218-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-218-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {ahmadifard, alireza and khosravi, hossei}, title = {A two step method for offline handwritten Farsi word recognition using adaptive division of gradient image}, abstract ={This paper presented a two step method for offline handwritten Farsi word recognition. In first step, in order to improve the recognition accuracy and speed, an algorithm proposed for initial eliminating lexicon entries unlikely to match the input image. For lexicon reduction, the words of lexicon are clustered using ISOCLUS and Hierarchal clustering algorithm. Clustering is based on the features that describe the shape of word generally. In second step, a new method proposed to extract histogram of gradient image which this showed well the correspondence between different samples of handwritten word images. The gradient feature vectors of input words are compared with gradient feature vectors of candidate words using K nearest neighbor classifications. The recognition result on handwritten words of IRANSHAR dataset showed that the lexicon reduction step and the new method of extracting gradient feature increased recognition accuracy and speed by removing classifier confusion.}, Keywords = {handwritten Farsi word recognition,ISOCLUS clustering algorithm,DTW algorithm, profile feature, gradient histogram feature}, volume = {12}, Number = {3}, pages = {15-29}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-66-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-66-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Sabahi, Mohammad Farz}, title = {Blind Detection and Equalization in Chaotic Communication Systems Using Importance Sampling}, abstract ={In this paper an Importance Sampling technique is proposed to achieve blind equalizer and detector for chaotic communication systems. Chaotic signals are generated with dynamic nonlinear systems. These signals have wide applications in communication due to their important properties like randomness, large bandwidth and unpredictability for long time. Based on the different chaotic signals properties, different communication methods have proposed such as chaotic modulation, masking, and spread spectrum. In this article, chaos masking is assumed for transmitting modulated message symbols. In this case, channel estimation is a nonlinear problem. Several methods such as extended Kalman filter (EKF), particle filter (PF), minimum nonlinear prediction error (MNPE) and ... are previously presented for this problem. Here, a new approach based on Monte Carlo sampling is proposed to joint channel estimation and demodulation. At the receiver end, Importance Sampling is used to detect binary symbols according to maximum likelihood criteria. Simulation results show that the proposed method has better performance especially in low SNR}, Keywords = {Chaotic Communication, Detection, Importance Sampling, Blind Equalization, Chaos Masking}, volume = {12}, Number = {3}, pages = {31-41}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-133-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-133-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Mirjalili, Alireza and Abootalebi, Vahid and Sadeghi, Mohammad Taghi}, title = {Improving the performance of sparse representation-based classifier for EEG classification}, abstract ={In this paper, the problem of classification of motor imagery EEG signals using a sparse representation-based classifier is considered. Designing a powerful dictionary matrix, i.e. extracting proper features, is an important issue in such a classifier. Due to its high performance, the Common Spatial Patterns (CSP) algorithm is widely used for this purpose in the BCI systems. The main disadvantages of the CSP algorithm are its sensibility to noise and the over learning phenomena when the number of training samples is limited. In this study, to overcome these problems, two modified form of the CSP algorithms, namely the DLRCSP and GLRCSP have been used. Using the adopted methods, the average detection rate is increased by a factor of about 7.78 %. Also, a problem of the SRC classifier which uses the standard BP algorithm is the computational complexity of the BP algorithm. To overcome this weakness, we used a new algorithm which is called the SL0 algorithm. Our classification results show that using the SL0 algorithm, the classification process is highly speeded up. Moreover, it leads to an increase of about 1.61% in average correct detection compared to the basic standard algorithm.}, Keywords = {Electroencephalogram, sparse representation-based classifier, regularized common spatial patterns, Smoothed L0-norm}, volume = {12}, Number = {3}, pages = {43-55}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-175-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-175-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Yazdani, Seyed Hamid and Abutalebi, Hamid Rez}, title = {Adaptive and Smart Beamforming in Ad-hoc Microphone Arrays by Clustering and Ranking of the Microphones}, abstract ={Considering the existence of a many speech degradation factors, speech enhancement has become an important topic in the field of speech processing. Beamforming is one of the well-known methods for improving the speech quality that is conventionally applied using regular (classical) microphone arrays. Due to the restrictions in the regular arrangement of microphones, in recent years there has been an emerging trend toward the microphone arrays with irregular arrangement (or so-called Ad-hoc microphone arrays). Due to the lack of knowledge about the location and the arrangement of microphones, and spreading of the microphones throughout the environment, the idea of clustering has been considered in this paper. We propose a method for the clustering of microphones in directional noise fields. For this type of noise fields, we propose a new clustering method that works based on the energy of the received signals. We have tried that the proposed clustering method to be applicable in different directional noise fields. We also propose a modified structure for the GSC beamformer by considering different roles for microphone clusters. Our evaluations indicate that in some situations, employing a microphone cluster produces superior results compared to the usage of all microphones. This, in turn, shows that the performance of the speech enhancement system can been improved using the clustering process, while the computational load is also decreased (due the reduction in the number of employed microphones).}, Keywords = {speech enhancement, beamforming, Ad-hoc microphone array, clustering, GSC beamformer}, volume = {12}, Number = {3}, pages = {57-68}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-202-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-202-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Sattarpour, Maryam and MohammadzadehAsl, Babak}, title = {}, abstract ={}, Keywords = {}, volume = {12}, Number = {3}, pages = {69-80}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-222-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-222-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Dehghani, Mehdi and Saleh, Mahmou}, title = {Design and evaluation of hybrid encoding schema for Covert Timing Channel on the Internet}, abstract ={Covert channel means communicating information through covering of overt and authorized channel in a manner that existence of channel to be hidden. In network covert timing channels that use timing features of transmission packets to modulating covert information, the appropriate encoding schema is very important. In this paper, a hybrid encoding schema proposed through combining "the inter-packets gap" and "the reordering packets" encoding schemas, emphasizing on improvement of capacity and stealthiness of covert channel. The capacity of proposed channel have computed and stealthness and robustness of channel have evaluated in experimental manner. Our results show that selecting 3 to 5 packet in a codword in accordance to normal situation of network traffic, the capacity is increased from 10% to 300% and stealthness is boosted up to acceptable value, and robustness is high enough.}, Keywords = {Covert Channel, Encoding, Performance Evaluation Criteria, Inter-packets gap, Reordering }, volume = {12}, Number = {3}, pages = {81-97}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-214-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-214-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Zarei, Farzaneh and Faili, Hesham and Mirian, Maryam}, title = {A machine learning approach for correcting the errors of a Treebank}, abstract ={The Treebank is one of the most useful resources for supervised or semi-supervised learning in many NLP tasks such as speech recognition, spoken language systems, parsing and machine translation. Treebank can be developded in different ways that could be, generally, categorized in manually and statistical approaches. While the resulted Treebank in each of these methods has the annotation error, one which accomplished by statistical method has much more errors than the other. Error in Treenabanks causes that they are not useful anymore. In this paper an statistical method is proposed which aims to correct the errors in a specific English LTAG-Treebank. The proposed method was applied to a automatically generated Treebank and an improvement from 68% to 79% respect to F-measure is retrieved.}, Keywords = {}, volume = {12}, Number = {3}, pages = {99-108}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-221-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-221-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Salehi, Marzieh and Khadivi, Shahram and Riahi, Nooshi}, title = {Confidence Estimation for Machine Translation using Novel Syntactic and Lexico-semantic Features}, abstract ={Despite machine translation (MT) wide suc-cess over last years, this technology is still not able to exactly translate text so that except for some language pairs in certain domains, post editing its output may take longer time than human translation. Nevertheless by having an estimation of the output quality, users can manage imperfection of this tech-nology. It means we need to estimate the confidence of the output without having any references. Moreover, Confidence Estimation (CE) can be useful for some applications that their goal is to improve machine translation quality such as system combination, regener-ating, pruning, etc. but there is not yet any completely satisfactory method for CE task. We propose 5 groups of syntactic and lexico-semantic features. The results show that the lexico-semantic feature outperforms the best baseline system (2) by 9.63% in CER, 8.5% in F-measure and 5.1% in negative class F-measure. Also by combining proposed syn-tactic features together we reach 4.59% CER reduction, 4.1% F-measure improvement and 2% negative F-measure improvement.}, Keywords = {confidence estimation, machine translation, mutual information, syntax, lexical, semantic.}, volume = {12}, Number = {3}, pages = {109-121}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-217-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-217-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2015} } @article{ author = {Marvasti-Zadeh, Seyed Mojtaba and Ghaneiyakhdan, Hossei}, title = {A Fast and Hybrid Boundary Matching Algorithm for Temporal Error Concealment of Video Data}, abstract ={Despite data resilient methods against error that are applied on video data in transmitter side, occurringerror along video data transferring for communication channels is inevitable. Error concealment is a useful method for improving the quality of damaged videos in receiver side. In this paper, a fast and hybrid boundary matching algorithm is presented for more accurate estimating of damaged motion vectors (MVs) from received video. The proposed algorithm performs the error concealment for each damaged macroblock (MB) according to the preference list of error concealment that it assigns. Then, boundary distortion for each candidate MBis calculated with classic and outer boundary matching criterionsfor each boundary pixel. After reconstructing of each damaged MB, the list of preference is updated. Moreover, depending on accuracy of each adjacent boundary from damaged MB, a special weight is given to them, through match process. Finally, the candidate MVwith the lowest boundary distortion is selected as MV of damaged MB. Experimental results show that the proposed algorithm increases the average of PSNR for different test sequences more than 1.8 dB in comparison with reference methods and without significant increasing in calculation time and with improving the quality of reconstructed videos.}, Keywords = {Temporal Error Concealment, Motion Vector Estimation, Hybrid Boundary Matching Algorithm, Macroblock}, volume = {12}, Number = {4}, pages = {3-15}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-173-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-173-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Rajabi, Hamid and Nahvi, Manoochehr}, title = {Fall Detection Using Novel Tracking Method Based on Modified Contour Algorithm}, abstract ={The population of elderly people has growing trend in the developed or developing countries. Since the elderly are mainly associated with disability, this group of people exposed to dangerous events such as falling down. It is therefore needed to take care of these people against dangerous events. Intelligent video monitoring is a approach that may be able to give quick notification to the caregivers. For this purpose, in this paper, an approach using a novel tracking method based on modified contour algorithm is presented. The new method is able to conduct tracking and falling down detection in a realistic conditions in the presence of multiple motions. Simulations indicate that the proposed algorithm is able to identify the fall-down event with high accuracy and speed.}, Keywords = {fall detection algorithm, contour, machine vision, tracking, intelligent surveillance systems.}, volume = {12}, Number = {4}, pages = {17-31}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-183-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-183-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {NematiNia, Mohammad Sadegh}, title = {Improving Heuristic Guess and Determine Attack on TIPSY and SNOW 1.0 Stream Ciphers}, abstract ={Guess and determine attacks are general attacks on stream ciphers. These attacks are classified into ad-hoc and Heuristic Guess and Determine (HGD) attacks. One of the Advantages of HGD attack algorithm over ad-hoc attack is that it is designed algorithmically for a large class of stream ciphers while being powerful. In this paper, we use auxiliary polynomials in addition to the original equations as the inputs to the HGD attack on TIPSY and SNOW 1.0 stream ciphers. Based on the concept of guessed basis, the number of guesses in both HGD attack and the improved one on TIPSY is six, however the attack complexity is reduced from O(2102)to O(296). This amount is equal to that of ad-hoc attack, but the size of the guessed basis is improved from seven to six. Also, the complexity of GD attack on SNOW 1.0 of heuristic one with the guessed basis of size 6 and ad-hoc attack with the guessed basis of size 7areO(2202) and O(2224), respectively. However, the complexity and the size of guessed basis of the improved HGD attack are reduced to O(2160) and 5, respectively.}, Keywords = {Stream Cipher, Guess and Determine attack, TIPSY, SNOW 1.0, Computational Complexity}, volume = {12}, Number = {4}, pages = {33-42}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-261-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-261-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {}, title = {Sharif Text Editor: A Persian Editor and Spell Checker System}, abstract ={In this paper, we will introduce an intelligent system to edit and spell check Persian texts. The goal is editing and preprocessing Persian texts for natural language processing tasks. This system is based on an expandable and engineering approach and is composed of three subsystems: Persian text editor, spell checker and stemmer. These parts interact with each other to edit texts. To do this, the stemmer subsystem process each word in the text if the subsystem could not find a stem in the lexicon, the word will be recognized as an incorrect word. Then, the spell checker provides a list of suggestions to correct the wrong word. Subsequently, the editor subsystem edits the text based on the standards of the Academy of Persian Language and Literature. Our evaluation shows nearly 92%, 95% and 96% precision numbers for editor, stemmer and spell checker subsystems, respectively.}, Keywords = {Key words: Natural Language Processing, automatic spell checking, text editor, stemmer}, volume = {12}, Number = {4}, pages = {43-52}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-250-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-250-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Ahmadkhani, Somayeh and Adibi, Peym}, title = {Supervised Probabilistic Principal Component Analysis Mixture Model in a Lossless Dimensionality Reduction Framework for Face Recognition}, abstract ={In this paper, we first proposed the supervised version of probabilistic principal component analysis mixture model. Then, we consider a learning predictive model with projection penalties, as an approach for dimensionality reduction without loss of information for face recognition. In the proposed method, first a local linear underlying manifold of data samples is obtained using the supervised probabilistic principal component analysis mixture model. Then, a support vector machine classifier with projection penalty is trained as a predictive model using this local linear manifold. Thus, the predictive model benefits from dimensionality reduction, while it loses minimum amount of useful information. To evaluate the proposed method, we used well-known face recognition databases. Gabor feature extraction method have been applied to these images. The experimental results show that the proposed method has a higher classification accuracy than many of the traditional methods which use predictive models after dimensionality reduction. It also works better than the projection penalty method with linear or nonlinear based dimensionality reduction models.}, Keywords = {Lossless Dimensionality Reduction, Mixture Model, Probabilistic Principal Component Analysis, Supervised, Projection Penalty}, volume = {12}, Number = {4}, pages = {53-65}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-259-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-259-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Fasahat, Foruzan and Payvandy, Pedram}, title = {Structural parameter extraction of warp and weft woven fabric using wavelet-fuzzy method and genetic algorithm}, abstract ={Flexibility of woven fabric structure has caused many errors in yarn location detection using customary methods of image processing. On this line, proposing an adaptive method with fabric image properties is concentrated to extract its parameters. In this regards, using meta-heuristic algorithms seems applicable to correspond extraction algorithm of structural parameters to the image conditions. In this study, a new method is proposed for woven fabric image preprocessing and structural texture detection applying compound methods of signal processing, fuzzy clustering and genetic algorithm. Results indicate that proposed method is capable of detecting exact yarn location with mean precision of more than 73 percent in double-layered fabric images with uneven color pattern. In one-layered fabric images with low density weave and invariable color pattern, the mean precision is more than 84 percent.}, Keywords = {Genetic Algorithm, Wavelet Transform, Fuzzy c-means (FCM) clustering, Image Processing, Fabric Image, Yarn Location.}, volume = {12}, Number = {4}, pages = {67-81}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-262-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-262-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {}, title = {automatic gender identification in persian text}, abstract ={Gigantic amount of textual data being transfers in web everyday. like other communities,cyberspace is vulnerable to attacks, false information and deception.it becomes increasingly important to design an efficient method to trace identity in this community.to investigate the problem of gender identification,we propose 48 feature,and design three machine learning algorithms.the results of study showed that ADtree classifier had accuracy up to 73.8%.}, Keywords = {,gender identification,author identification,text mining}, volume = {12}, Number = {4}, pages = {83-94}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-104-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-104-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Soltanzadeh, Fatemeh and Bahrani, Mohammad and Eslami, Moharram}, title = {A Rule-Based Approach in Converting a Dependency Parse Tree into Phrase Structure Parse Tree for Persian}, abstract ={In this paper, an automatic method in converting a dependency parse tree into an equivalent phrase structure one, is introduced for the Persian language. In first step, a rule-based algorithm was designed. Then, Persian specific dependency-to-phrase structure conversion rules merged to the algorithm. Subsequently, the Persian dependency treebank with about 30,000 sentences was used as an input for the algorithm and an equivalent phrase structure treebank was extracted. Finally, the statistical Stanford parser was trained using the developed treebank. Experimental results show a F1 of 96.05% for the conversion algorithm and an F1 of 86.01% for Persian factored model parser.}, Keywords = {Conversion, Dependency Grammar, Phrase Structure Grammar, Natural Language Processing, Treebank, Persian. }, volume = {12}, Number = {4}, pages = {95-115}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-272-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-272-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {rahatighochani, saei}, title = {farsi word sense disambiguation with LDA Topic model}, abstract ={Word sense disambiguation is the task of identifying the correct sense for the word in a given context among a finite set of possible sense. In this paper a model for farsi word sense disambiguation is presented. The model use two group of features: first, all word and stop words around target word and topic models as second features. We extract topics from a farsi corpus with Latent Dirichlet Allocation (LDA) model. The system with a maximum entropy model achieved 97.67% precision for 4 high frequently farsi homograph words}, Keywords = {Latent Dirichlet Allocation(LDA), Topic Model, Maximum Entropy, Word Sense Disambiguation }, volume = {12}, Number = {4}, pages = {117-125}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-58-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-58-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} }