Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310510
Sepehr Seifi, H. Karimi
This paper presents the stability analysis for a single-phase phase-locked loop (PLL) for power systems applications. The dynamical equations of a previously presented single-phase PLL are systematically derived and linearized for design and stability analysis purposes. Based on the linearized model of the PLL, parameters of the loop filter and the PI controller are accurately determined. The main advantages of the PI controller are discussed as well as its design procedure. Moreover, it is shown that, unlike the conventional single-phase PLLs, the mentioned PLL does not suffer from double-frequency ripples. Simulations carried out in MATLAB and SIMULINK verify the performance of the PLL under various operational scenarios; features like frequency and magnitude tracking, noise immunity, and harmonic attenuation are observed.
{"title":"Stability analysis of a single-phase phase-locked loop for power systems applications","authors":"Sepehr Seifi, H. Karimi","doi":"10.1109/ISSPA.2012.6310510","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310510","url":null,"abstract":"This paper presents the stability analysis for a single-phase phase-locked loop (PLL) for power systems applications. The dynamical equations of a previously presented single-phase PLL are systematically derived and linearized for design and stability analysis purposes. Based on the linearized model of the PLL, parameters of the loop filter and the PI controller are accurately determined. The main advantages of the PI controller are discussed as well as its design procedure. Moreover, it is shown that, unlike the conventional single-phase PLLs, the mentioned PLL does not suffer from double-frequency ripples. Simulations carried out in MATLAB and SIMULINK verify the performance of the PLL under various operational scenarios; features like frequency and magnitude tracking, noise immunity, and harmonic attenuation are observed.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"19 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":"128578579","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.2012.6310521
Mohamed Ali Bouker, É. Hervet
Content-based indexing of images consists in extracting visual information from digital images (such as pixels, colors, objects, shapes, etc.), and can be performed automatically and fast by computers. This work focuses on color indexing of images. A statistical algorithm called Mean-Shift is used to modelize the color distributions of images as two-dimensional Gaussian kernels. The experiments have been performed on the COIL1 database and the results show that the proposed method compares well to other content-based retrieval methods.
{"title":"Image retrieval based on mean-shift clustering using color descriptor","authors":"Mohamed Ali Bouker, É. Hervet","doi":"10.1109/ISSPA.2012.6310521","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310521","url":null,"abstract":"Content-based indexing of images consists in extracting visual information from digital images (such as pixels, colors, objects, shapes, etc.), and can be performed automatically and fast by computers. This work focuses on color indexing of images. A statistical algorithm called Mean-Shift is used to modelize the color distributions of images as two-dimensional Gaussian kernels. The experiments have been performed on the COIL1 database and the results show that the proposed method compares well to other content-based retrieval methods.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"87 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":"128959235","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.2012.6310466
Graeme A. Jones, T. Nohara
For most of its existence, radar has been a tool for real-time observation and processing. Indeed, most signal processing aspects of radar analysis were concerned with real-time detection, filtering, clutter rejection, tracking and targeting. This paper outlines the application of radar in a networked environment, which becomes much more than a real-time feed-forward system. It incorporates many and varied aspects of signal and information processing, from tracking and fusion, through to statistical analysis and data mining. These networks have been deployed and are operating in different fields of application, and some of these real-world examples will be presented herein.
{"title":"Wide area radar networks with data persistence","authors":"Graeme A. Jones, T. Nohara","doi":"10.1109/ISSPA.2012.6310466","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310466","url":null,"abstract":"For most of its existence, radar has been a tool for real-time observation and processing. Indeed, most signal processing aspects of radar analysis were concerned with real-time detection, filtering, clutter rejection, tracking and targeting. This paper outlines the application of radar in a networked environment, which becomes much more than a real-time feed-forward system. It incorporates many and varied aspects of signal and information processing, from tracking and fusion, through to statistical analysis and data mining. These networks have been deployed and are operating in different fields of application, and some of these real-world examples will be presented herein.","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":"124704729","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.2012.6310495
S. Meudt, Lutz Bigalke, F. Schwenker
In this paper we present ATLAS, a new graphical tool for annotation of multi-modal data streams. Although Atlas has been developed for data bases collected in human computer interaction (HCI) scenarios, it is applicable for multimodal time series in general settings. In our HCI scenario, besides multi-channel audio and video inputs, various bio-physiological data has been recorded, e.g. complex multi-variate signals such as ECG, EEG, EMG as well as simple uni-variate skin conductivity, respiration, blood volume pulse, etc. All these different types of data can be processed through ATLAS. In addition to processing raw data, intermediate data processing results, such as extracted features, and even (probabilistic or crisp) outputs of pre-trained classifier modules can be displayed. Furthermore, annotation and transcription tools have been implemented. ATLAS's basic structure is briefly described. Besides these basic annotation features, active learning (active data selection) approaches have been included into the overall system. Support Vector Machines (SVM) utilizing probabilistic outputs are the current algorithms to select confident data. Confident classification results made by the SVM classifier support the human expert to investigate unlabeled parts of the data.
{"title":"Atlas - Annotation tool using partially supervised learning and multi-view co-learning in human-computer-interaction scenarios","authors":"S. Meudt, Lutz Bigalke, F. Schwenker","doi":"10.1109/ISSPA.2012.6310495","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310495","url":null,"abstract":"In this paper we present ATLAS, a new graphical tool for annotation of multi-modal data streams. Although Atlas has been developed for data bases collected in human computer interaction (HCI) scenarios, it is applicable for multimodal time series in general settings. In our HCI scenario, besides multi-channel audio and video inputs, various bio-physiological data has been recorded, e.g. complex multi-variate signals such as ECG, EEG, EMG as well as simple uni-variate skin conductivity, respiration, blood volume pulse, etc. All these different types of data can be processed through ATLAS. In addition to processing raw data, intermediate data processing results, such as extracted features, and even (probabilistic or crisp) outputs of pre-trained classifier modules can be displayed. Furthermore, annotation and transcription tools have been implemented. ATLAS's basic structure is briefly described. Besides these basic annotation features, active learning (active data selection) approaches have been included into the overall system. Support Vector Machines (SVM) utilizing probabilistic outputs are the current algorithms to select confident data. Confident classification results made by the SVM classifier support the human expert to investigate unlabeled parts of the data.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"4 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":"130513902","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.2012.6310693
M. Landolsi
The paper addresses the performance analysis of pulse-shaped direct-sequence ultra-wideband (UWB) communication systems employing offset quadrature phase shit keying (OQPSK). The proposed system offers many advantages over carrier-less UWB schemes, as pulse-shaped OQPSK spreading gives better phase randomization in multi-user interference scenarios, and is also useful for minimizing large phase jumps in the modulated signals, which reduces spectral re-growth and adjacent channel interference, particularly in the presence of non-linear amplifiers. Bit error probability results are derived for fading channels with selection diversity and maximum ratio combining receivers. Numerical examples with pulse shapes based on Gaussian monocycle derivatives and modified Hermite polynomials are given to illustrate the relative performance comparisons among different chip pulse shapes and diversity combining techniques.
{"title":"Pulse shaping for direct-sequence offset quadrature-spread UWB communication signals","authors":"M. Landolsi","doi":"10.1109/ISSPA.2012.6310693","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310693","url":null,"abstract":"The paper addresses the performance analysis of pulse-shaped direct-sequence ultra-wideband (UWB) communication systems employing offset quadrature phase shit keying (OQPSK). The proposed system offers many advantages over carrier-less UWB schemes, as pulse-shaped OQPSK spreading gives better phase randomization in multi-user interference scenarios, and is also useful for minimizing large phase jumps in the modulated signals, which reduces spectral re-growth and adjacent channel interference, particularly in the presence of non-linear amplifiers. Bit error probability results are derived for fading channels with selection diversity and maximum ratio combining receivers. Numerical examples with pulse shapes based on Gaussian monocycle derivatives and modified Hermite polynomials are given to illustrate the relative performance comparisons among different chip pulse shapes and diversity combining techniques.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"27 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":"123205707","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.2012.6310547
V. Chandran
Time-varying bispectra, computed using a classical sliding window short-time Fourier approach, are analyzed for scalp EEG potentials evoked by an auditory stimulus and new observations are presented. A single, short duration tone is presented from the left or the right, direction unknown to the test subject. The subject responds by moving the eyes to the direction of the sound. EEG epochs sampled at 200 Hz for repeated trials are processed between -70 ms and +1200 ms with reference to the stimulus. It is observed that for an ensemble of correctly recognized cases, the best matching time-varying bispectra at (8 Hz, 8Hz) are for PZ-FZ channels and this is also largely the case for grand averages but not for power spectra at 8 Hz. Out of 11 subjects, the only exception for time-varying bispectral match was a subject with family history of Alzheimer's disease and the difference was in bicoherence, not biphase.
{"title":"Time-varying bispectral analysis of auditory evoked multi-channel scalp EEG","authors":"V. Chandran","doi":"10.1109/ISSPA.2012.6310547","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310547","url":null,"abstract":"Time-varying bispectra, computed using a classical sliding window short-time Fourier approach, are analyzed for scalp EEG potentials evoked by an auditory stimulus and new observations are presented. A single, short duration tone is presented from the left or the right, direction unknown to the test subject. The subject responds by moving the eyes to the direction of the sound. EEG epochs sampled at 200 Hz for repeated trials are processed between -70 ms and +1200 ms with reference to the stimulus. It is observed that for an ensemble of correctly recognized cases, the best matching time-varying bispectra at (8 Hz, 8Hz) are for PZ-FZ channels and this is also largely the case for grand averages but not for power spectra at 8 Hz. Out of 11 subjects, the only exception for time-varying bispectral match was a subject with family history of Alzheimer's disease and the difference was in bicoherence, not biphase.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"65 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":"123608455","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.2012.6310604
Juan Sebastian Hurtado Jaramillo, D. Guarín, Á. Orozco
In the following article, Pseudo-Periodic surrogate data method is described as a tool to detect the underlying dynamics existing in non-linear phenomena, in order to know beforehand the best approach when analyzing with these types of time series. This method is applied to voice signals, a non-linear phenomenon observed from the vocal tract, to try determine its underlying dynamic structure and therefore use the appropriate approach. Lempel-Ziv complexity, based on the counting of sequences, and Sample Entropy, based on the extent of the irregularity in a signal, are introduced as discriminating statistics for null hypothesis testing within the surrogate data method. In addition, a methodology is explained on how to apply this method to voice signals. Our results showed that Lempel-Ziv complexity rejects the proposed hypothesis while sample entropy gives results beyond expectation.
{"title":"Pseudo-periodic surrogate data method on voice signals","authors":"Juan Sebastian Hurtado Jaramillo, D. Guarín, Á. Orozco","doi":"10.1109/ISSPA.2012.6310604","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310604","url":null,"abstract":"In the following article, Pseudo-Periodic surrogate data method is described as a tool to detect the underlying dynamics existing in non-linear phenomena, in order to know beforehand the best approach when analyzing with these types of time series. This method is applied to voice signals, a non-linear phenomenon observed from the vocal tract, to try determine its underlying dynamic structure and therefore use the appropriate approach. Lempel-Ziv complexity, based on the counting of sequences, and Sample Entropy, based on the extent of the irregularity in a signal, are introduced as discriminating statistics for null hypothesis testing within the surrogate data method. In addition, a methodology is explained on how to apply this method to voice signals. Our results showed that Lempel-Ziv complexity rejects the proposed hypothesis while sample entropy gives results beyond expectation.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"43 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":"114834951","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.2012.6310553
Esmaeil Faramarzi, D. Rajan, M. Christensen
In this paper, a new method for reconstructing a video of higher spatial and temporal resolutions from multiple low-resolution video sequences is introduced. The proposed cost function includes a new space-time regularization term based upon Huber-Markov random field (HMRF) model which is convex but non-quadratic. However, this prior can be efficiently and accurately approximated by a quadratic form through an iterative process. This regularization form is a type of variational integral that exploits the piecewise smoothness nature of high-resolution images. We also address in detail the main reason for appearance of the so called “ghosting effect” in the temporal super-resolution reconstruction and explain how it can be resolved.
{"title":"Space-time super-resolution from multiple-videos","authors":"Esmaeil Faramarzi, D. Rajan, M. Christensen","doi":"10.1109/ISSPA.2012.6310553","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310553","url":null,"abstract":"In this paper, a new method for reconstructing a video of higher spatial and temporal resolutions from multiple low-resolution video sequences is introduced. The proposed cost function includes a new space-time regularization term based upon Huber-Markov random field (HMRF) model which is convex but non-quadratic. However, this prior can be efficiently and accurately approximated by a quadratic form through an iterative process. This regularization form is a type of variational integral that exploits the piecewise smoothness nature of high-resolution images. We also address in detail the main reason for appearance of the so called “ghosting effect” in the temporal super-resolution reconstruction and explain how it can be resolved.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"2 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":"124071119","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.2012.6310700
S. Suvorova, T. Vaithianathan, T. Caelli
Inertial sensors, such as accelerometers and gyroscopes, are rarely used by themselves to compute velocity and position as each requires the integration of very noisy data. The variance and bias in the resulting position and velocity estimates grow unbounded in time. This paper proposes a solution to provide a de-biased and de-noised estimation of position and velocity of human actions from accelerometer measurements. The method uses a continuous wavelet transform applied to the measurements recursively to provide reliable action trajectory reconstruction. The results are presented from experiments performed with a MEMS accelerometer and gyroscope.
{"title":"Action trajectory reconstruction from inertial sensor measurements","authors":"S. Suvorova, T. Vaithianathan, T. Caelli","doi":"10.1109/ISSPA.2012.6310700","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310700","url":null,"abstract":"Inertial sensors, such as accelerometers and gyroscopes, are rarely used by themselves to compute velocity and position as each requires the integration of very noisy data. The variance and bias in the resulting position and velocity estimates grow unbounded in time. This paper proposes a solution to provide a de-biased and de-noised estimation of position and velocity of human actions from accelerometer measurements. The method uses a continuous wavelet transform applied to the measurements recursively to provide reliable action trajectory reconstruction. The results are presented from experiments performed with a MEMS accelerometer and gyroscope.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"96 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":"126571351","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.2012.6310462
Florin-Marian Birleanu, I. Candel, C. Ioana, C. Gervaise, A. Serbanescu, G. Serban
The detection and characterization of burst signals are challenging tasks for time-frequency analysis, due to their very short duration. This paper investigates in this context the recurrence plot analysis (RPA) method, from which it derives the vector samples processing (VeSP) concept. The paper shows that VeSP is a generic framework that unifies signal processing concepts like histogram and autocorrelation, which it also generalizes and extends. Results of VeSP based tools are provided, concerning detection of transient signals, noise reduction, and frequency estimation.
{"title":"A vector approach to transient signal processing","authors":"Florin-Marian Birleanu, I. Candel, C. Ioana, C. Gervaise, A. Serbanescu, G. Serban","doi":"10.1109/ISSPA.2012.6310462","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310462","url":null,"abstract":"The detection and characterization of burst signals are challenging tasks for time-frequency analysis, due to their very short duration. This paper investigates in this context the recurrence plot analysis (RPA) method, from which it derives the vector samples processing (VeSP) concept. The paper shows that VeSP is a generic framework that unifies signal processing concepts like histogram and autocorrelation, which it also generalizes and extends. Results of VeSP based tools are provided, concerning detection of transient signals, noise reduction, and frequency estimation.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"24 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":"128066868","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：