Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310460
I. Orović, A. Draganic, S. Stankovic, E. Sejdić
A unified approach for the estimation of the first three phase derivatives of non-stationary signals is proposed in this paper. The possibility to accurately estimate phase derivatives is important in many applications dealing with objects velocity, acceleration and acceleration rate, such as the radar applications and mechanics. The estimation approach is based on definition of the complex-lag distribution. The proposed distribution is inspired by the concepts of complex analysis theory. The general form of distribution for the estimation of the first, second and third derivative of the phase is derived from the specific individual cases. The theoretical considerations are illustrated in the example with fast varying signal phase function.
{"title":"A unified approach for the estimation of instantaneous frequency and its derivatives for non-stationary signals analysis","authors":"I. Orović, A. Draganic, S. Stankovic, E. Sejdić","doi":"10.1109/ISSPA.2012.6310460","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310460","url":null,"abstract":"A unified approach for the estimation of the first three phase derivatives of non-stationary signals is proposed in this paper. The possibility to accurately estimate phase derivatives is important in many applications dealing with objects velocity, acceleration and acceleration rate, such as the radar applications and mechanics. The estimation approach is based on definition of the complex-lag distribution. The proposed distribution is inspired by the concepts of complex analysis theory. The general form of distribution for the estimation of the first, second and third derivative of the phase is derived from the specific individual cases. The theoretical considerations are illustrated in the example with fast varying signal phase function.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"334 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123402035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310485
R. F. Moghaddam, F. F. Moghaddam, M. Cheriet
A framework for development of segmentation-free optical recognizers of ancient manuscripts, which work free from line, word, and character segmentation, is proposed. The framework introduces a new representation of visual text using the concept of signature patches. These patches which are free from traditional guidelines of text, such as the baseline, are registered to each other using a microscale registration method based on the estimation of the active regions using a multilevel classifier, the directional map. Then, an one-dimensional feature vector is extracted from the registered signature patches, named spiral features. The incremental learning process is performed using a sparse representation using a dictionary of spiral feature atoms. The framework is applied to the George Washington database with promising results.
{"title":"A new framework based on signature patches, micro registration, and sparse representation for optical text recognition","authors":"R. F. Moghaddam, F. F. Moghaddam, M. Cheriet","doi":"10.1109/ISSPA.2012.6310485","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310485","url":null,"abstract":"A framework for development of segmentation-free optical recognizers of ancient manuscripts, which work free from line, word, and character segmentation, is proposed. The framework introduces a new representation of visual text using the concept of signature patches. These patches which are free from traditional guidelines of text, such as the baseline, are registered to each other using a microscale registration method based on the estimation of the active regions using a multilevel classifier, the directional map. Then, an one-dimensional feature vector is extracted from the registered signature patches, named spiral features. The incremental learning process is performed using a sparse representation using a dictionary of spiral feature atoms. The framework is applied to the George Washington database with promising results.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123551733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310576
Erik Blasch, Jianbo Gao, W. Tung
Multiscale image processing is a powerful technique that can determine image characteristics (e.g. clutter), provide denoising, and determine object features. Imagery is highly nonstationary (i.e. mean and variance change with location and time) and multiscaled (i.e. dependent on the spatial or temporal interval lengths). In this paper, we utilize the scale-dependent Lyapunov exponent (SDLE), which unifies the principles of fractal and chaos theory, to characterize the different signal behaviors on a wide range of scales simultaneously. Commonly used complexity measures, including those from information theory, chaos theory, and random fractal theory, can all be related to the values of the SDLE at specific scales, and therefore, SDLE can act as the basis for a unified theory of multiscale analysis of complex imagery data. We describe the power-law and singular-value decomposition (SVD) for image processing and demonstrate a SDLE example using TeraHertz (THz) imagery for concealed target image fusion.
{"title":"Chaos-based image assessment for THz imagery","authors":"Erik Blasch, Jianbo Gao, W. Tung","doi":"10.1109/ISSPA.2012.6310576","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310576","url":null,"abstract":"Multiscale image processing is a powerful technique that can determine image characteristics (e.g. clutter), provide denoising, and determine object features. Imagery is highly nonstationary (i.e. mean and variance change with location and time) and multiscaled (i.e. dependent on the spatial or temporal interval lengths). In this paper, we utilize the scale-dependent Lyapunov exponent (SDLE), which unifies the principles of fractal and chaos theory, to characterize the different signal behaviors on a wide range of scales simultaneously. Commonly used complexity measures, including those from information theory, chaos theory, and random fractal theory, can all be related to the values of the SDLE at specific scales, and therefore, SDLE can act as the basis for a unified theory of multiscale analysis of complex imagery data. We describe the power-law and singular-value decomposition (SVD) for image processing and demonstrate a SDLE example using TeraHertz (THz) imagery for concealed target image fusion.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131962540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310570
A. Mansour
This manuscript deals with the estimation of probability density functions. This topic is very important in applied mathematics due to its various applications: Blind identification, blind Separation of Sources, risk theory, game theory, statistical modeling, etc. Since the mid of the 20th century, various solutions have been proposed in order to estimate probability density functions of latent variables and random variables. Hereinafter, a brief survey of major approaches is presented. Meanwhile, we prove that most of proposed methods could be considered as kernel density estimation methods. Theoretical proof for a previously used simulation model is also presented. The application of classic estimators to non-stationary signals is also considered. Finally, simulations are presented and discussed.
{"title":"Probability density function estimators applied to non-stationary signals","authors":"A. Mansour","doi":"10.1109/ISSPA.2012.6310570","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310570","url":null,"abstract":"This manuscript deals with the estimation of probability density functions. This topic is very important in applied mathematics due to its various applications: Blind identification, blind Separation of Sources, risk theory, game theory, statistical modeling, etc. Since the mid of the 20th century, various solutions have been proposed in order to estimate probability density functions of latent variables and random variables. Hereinafter, a brief survey of major approaches is presented. Meanwhile, we prove that most of proposed methods could be considered as kernel density estimation methods. Theoretical proof for a previously used simulation model is also presented. The application of classic estimators to non-stationary signals is also considered. Finally, simulations are presented and discussed.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115019096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310543
Mathias M. Adankon, J. Dansereau, H. Labelle, F. Cheriet
This paper describes a method for analyzing scoliosis trunk deformities using Independent Component Analysis (ICA). Our hypothesis is that ICA can capture the scoliosis deformities visible on the trunk. Unlike Principal Component Analysis (PCA), ICA gives local shape variation and assumes that the data distribution is not normal. 3D torso images of 56 subjects including 28 patients with adolescent idiopathic scoliosis and 28 healthy subjects are analyzed using ICA. First, we remark that the independent components capture the local scoliosis deformities as the shoulder variation, the scapula asymmetry and the waist deformation. Second, we note that the different scoliosis curve types are characterized by different combinations of specific independent components.
{"title":"Analysis of scoliosis trunk deformities using ICA","authors":"Mathias M. Adankon, J. Dansereau, H. Labelle, F. Cheriet","doi":"10.1109/ISSPA.2012.6310543","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310543","url":null,"abstract":"This paper describes a method for analyzing scoliosis trunk deformities using Independent Component Analysis (ICA). Our hypothesis is that ICA can capture the scoliosis deformities visible on the trunk. Unlike Principal Component Analysis (PCA), ICA gives local shape variation and assumes that the data distribution is not normal. 3D torso images of 56 subjects including 28 patients with adolescent idiopathic scoliosis and 28 healthy subjects are analyzed using ICA. First, we remark that the independent components capture the local scoliosis deformities as the shoulder variation, the scapula asymmetry and the waist deformation. Second, we note that the different scoliosis curve types are characterized by different combinations of specific independent components.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114953358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310632
M. I. Akram, A. Sheikh
An efficient implementation of the linear Finite Impulse Response (FIR) Filter has been performed over the Texas Instrument (TI) TMS320C6416 fixed point Digital Signal Processor (DSP) platform. The implementation fully exploits the pipelined architecture of the processor along with the circular buffering to gain the speed factor of 7 times than the reference approach hence making this more suitable for high speed real-time signal processing applications involving tap delay line (TDL) model.
{"title":"Efficient implementation of tap delay line filter using high speed Digital Signal Processor","authors":"M. I. Akram, A. Sheikh","doi":"10.1109/ISSPA.2012.6310632","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310632","url":null,"abstract":"An efficient implementation of the linear Finite Impulse Response (FIR) Filter has been performed over the Texas Instrument (TI) TMS320C6416 fixed point Digital Signal Processor (DSP) platform. The implementation fully exploits the pipelined architecture of the processor along with the circular buffering to gain the speed factor of 7 times than the reference approach hence making this more suitable for high speed real-time signal processing applications involving tap delay line (TDL) model.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"403 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134097346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310691
M. Bouri
In this paper, we introduce new technique for localization of narrowband signals. We propose two new versions of the propagator method. Using its algebraic properties, the cross-spectral matrix (CSM) is replaced by the upper triangular matrix (UTM) obtained from the LU or QR factorization of the CSM. The upper triangular matrices are partitioned to estimate the propagator. The LU factorization and Householder QR factorization algorithms need N3/3 and 2N3/3 floating point operations, respectively. The triangular factorization technique can reduce the complexity when compared to eigen subspace method such as MUSIC algorithm requires N3. Simulation results are presented to verify the effectiveness of the proposed methods.
{"title":"New versions of the propagator method","authors":"M. Bouri","doi":"10.1109/ISSPA.2012.6310691","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310691","url":null,"abstract":"In this paper, we introduce new technique for localization of narrowband signals. We propose two new versions of the propagator method. Using its algebraic properties, the cross-spectral matrix (CSM) is replaced by the upper triangular matrix (UTM) obtained from the LU or QR factorization of the CSM. The upper triangular matrices are partitioned to estimate the propagator. The LU factorization and Householder QR factorization algorithms need N3/3 and 2N3/3 floating point operations, respectively. The triangular factorization technique can reduce the complexity when compared to eigen subspace method such as MUSIC algorithm requires N3. Simulation results are presented to verify the effectiveness of the proposed methods.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"18 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132737431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310459
T. Fillon, J. Prado
In this article, a new Constant-Q transform implementation is proposed together with a generalization of both the Short-Term Fourier Transform and the Constant-Q transform. The purpose of this generalization is to provide a discrete time-frequency analysis tool with arbitrary center frequency and frequency resolution for each bin of the transform. This new analysis framework is very flexible and can be related to many common time-frequency transforms. Furthermore, new interesting transforms with specific time-frequency resolutions can be defined. To illustrate and validate the corresponding approach, experimental results and examples are provided for different configurations.
{"title":"A flexible multi-resolution time-frequency analysis framework for audio signals","authors":"T. Fillon, J. Prado","doi":"10.1109/ISSPA.2012.6310459","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310459","url":null,"abstract":"In this article, a new Constant-Q transform implementation is proposed together with a generalization of both the Short-Term Fourier Transform and the Constant-Q transform. The purpose of this generalization is to provide a discrete time-frequency analysis tool with arbitrary center frequency and frequency resolution for each bin of the transform. This new analysis framework is very flexible and can be related to many common time-frequency transforms. Furthermore, new interesting transforms with specific time-frequency resolutions can be defined. To illustrate and validate the corresponding approach, experimental results and examples are provided for different configurations.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"53 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134064455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310554
N. Beaulieu, D. J. Young
Ultra-wideband (UWB) wireless technologies have the potential to greatly improve the quality of short-range communications between unlicensed wireless devices. By exploiting huge bandwidth, UWB devices can overcome the spectral congestion and performance impairments experienced by narrowband devices operating in common unlicensed frequency bands. On the other hand, strict constraints on the signal power spectral density must be enforced to limit spectral emissions, so while UWB is unlicensed, the properties of transmitted signals must be regulated. In the impulse radio (IR) class of UWB systems, a number of pulses are used to transmit one information symbol and the pulses are randomly time-shifted within a frame structure to avoid collisions with other users. Low power spectral density is maintained by transmitting many pulses and the receiver integrates the pulses to achieve sufficient energy for low error rates. Impulse radio systems employing such time-hopping (TH) and repetition code designs are characterized by low duty cycle transmission, with transmitted signal energy occupying only a small fraction of the available transmission time. Although the TH scheme is intended to prevent catastrophic interference between multiuser TH-UWB transmissions, multiple-user interference (MUI) can impair uncoordinated transmissions in applications where several UWB devices are located at close range. In this talk, we show that the signal processing adopted in conventional UWB receivers does not fully exploit the TH code and has poor performance in the presence of significant MUI. Statistical signal processing based on the properties of MUI in TH-UWB is discussed, and two classes of techniques for mitigation of MUI are presented. The first class uses statistical characterizations of the MUI-plus-AWGN disturbance in the received THUWB signals as a basis for statistical receiver processing structures. The second class uses intuitive interference-sensing techniques specifically developed for the low duty cycle TH-UWB signal format, which control the processing of pulse replicas at the receiver. Both methods lead to greatly improved bit error rate performance compared to the conventional receiver processing. Both types of interference mitigation can be powerfully and efficiently used in a single receiver, and composite receiver designs that provide superior performance are discussed.
{"title":"Statistical and intuitive nonlinear signal processing designs for multiuser interference mitigation in UWB systems","authors":"N. Beaulieu, D. J. Young","doi":"10.1109/ISSPA.2012.6310554","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310554","url":null,"abstract":"Ultra-wideband (UWB) wireless technologies have the potential to greatly improve the quality of short-range communications between unlicensed wireless devices. By exploiting huge bandwidth, UWB devices can overcome the spectral congestion and performance impairments experienced by narrowband devices operating in common unlicensed frequency bands. On the other hand, strict constraints on the signal power spectral density must be enforced to limit spectral emissions, so while UWB is unlicensed, the properties of transmitted signals must be regulated. In the impulse radio (IR) class of UWB systems, a number of pulses are used to transmit one information symbol and the pulses are randomly time-shifted within a frame structure to avoid collisions with other users. Low power spectral density is maintained by transmitting many pulses and the receiver integrates the pulses to achieve sufficient energy for low error rates. Impulse radio systems employing such time-hopping (TH) and repetition code designs are characterized by low duty cycle transmission, with transmitted signal energy occupying only a small fraction of the available transmission time. Although the TH scheme is intended to prevent catastrophic interference between multiuser TH-UWB transmissions, multiple-user interference (MUI) can impair uncoordinated transmissions in applications where several UWB devices are located at close range. In this talk, we show that the signal processing adopted in conventional UWB receivers does not fully exploit the TH code and has poor performance in the presence of significant MUI. Statistical signal processing based on the properties of MUI in TH-UWB is discussed, and two classes of techniques for mitigation of MUI are presented. The first class uses statistical characterizations of the MUI-plus-AWGN disturbance in the received THUWB signals as a basis for statistical receiver processing structures. The second class uses intuitive interference-sensing techniques specifically developed for the low duty cycle TH-UWB signal format, which control the processing of pulse replicas at the receiver. Both methods lead to greatly improved bit error rate performance compared to the conventional receiver processing. Both types of interference mitigation can be powerfully and efficiently used in a single receiver, and composite receiver designs that provide superior performance are discussed.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129460523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310627
I. A. Arriaga-Trejo, A. Orozco-Lugo, Arturo Veloz-Guerrero, Manuel E. Guzman-Renteria
In this paper, the training sequence synchronization (TSS) problem for Widely Linear (WL) system estimation is addressed. This problem appears when superimposed training (ST) is considered as the methodology to perform the identification of WL systems. The proposed method exploits the ciclostationarity induced in the process at the output of the WL system when training sequences generating circulant augmented matrices are employed. Unlike strictly linear (SL) systems, where the delay required to achieve synchronization is unique, for WL systems two possible solutions appear. It is here shown that the correct synchronization delay can be distinguished if further characteristics of the WL system are known in advance.
{"title":"Superimposed training synchronization for Widely Linear systems","authors":"I. A. Arriaga-Trejo, A. Orozco-Lugo, Arturo Veloz-Guerrero, Manuel E. Guzman-Renteria","doi":"10.1109/ISSPA.2012.6310627","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310627","url":null,"abstract":"In this paper, the training sequence synchronization (TSS) problem for Widely Linear (WL) system estimation is addressed. This problem appears when superimposed training (ST) is considered as the methodology to perform the identification of WL systems. The proposed method exploits the ciclostationarity induced in the process at the output of the WL system when training sequences generating circulant augmented matrices are employed. Unlike strictly linear (SL) systems, where the delay required to achieve synchronization is unique, for WL systems two possible solutions appear. It is here shown that the correct synchronization delay can be distinguished if further characteristics of the WL system are known in advance.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129631272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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