{"title":"Identifying individuals using ECG beats","authors":"Ramaswamy Palaniappan, Shankar M. Krishnan","doi":"10.1109/SPCOM.2004.1458524","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458524","url":null,"abstract":"In this paper, we propose a technique to identify individuals using features extracted from QRS segment of electrocardiogram (ECG) signals. A total of 2000 samples from 10 subjects from the Arrhythmia Laboratory at Boston's Beth Israel Hospital (now the Beth Israel Deaconess Medical Center) database were used. These data are available as MIT-BH Normal Sinus Rhythm database and consist of 18 hour long-term recordings with 2 ECG signals. The commonly used features like R-R interval, R amplitude, QRS interval, QR amplitude and RS amplitude were used. In addition to these features, we propose the use of form factor of the QRS segment. Form factor has been used previously in electroencephalogram analysis and it is a measure of the complexity of the signal. These six features were then used by two neural network classifiers: multilayer perceptron-backpropagation (MLP-BP) and simplified fuzzy ARTMAP (SFA). The data were split equally for MLP-BP and SFA training and testing. The results gave classification performance up to 97.6%. This indicates that ECG has the potential to be used as a biometric tool.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125214500","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}
{"title":"Image denoising and detail preservation by probabilistic models","authors":"T. Liu, Huiyu Zhou, F. Lin, Y. Pang, Ji Wu","doi":"10.1109/SPCOM.2004.1458403","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458403","url":null,"abstract":"In this paper, we present a novel noise suppression and detail preservation algorithm. As a first step, the test image is pre-processed through a multiresolution analysis employing the discrete wavelet transform. Then, we design a fast and robust total variation technique, incorporating a statistical representation in the style of maximum likelihood estimation. Finally, we compare this proposed approach to current state-of-the-art denoising methods applied on synthetic and real images. The results demonstrate the encouraging performance of our algorithm.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130848887","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}
{"title":"Data association for multi target-multi model particle filtering: implicit assignment to weighted assignment","authors":"M. Zaveri, U. Desai, S. Merchant","doi":"10.1109/SPCOM.2004.1458350","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458350","url":null,"abstract":"In multiple target tracking the data association, i.e. observation to track assignment and the model selection to track arbitrary trajectory play an important role for success of any tracking algorithm. In this paper we propose various methods for data association in the presence of multiple targets and dense clutter along with the tracking algorithm using multiple model based particle filtering. Particle filtering allows one to use non-linear/non-Gaussian state space model for target tracking. Data association problem is solved using (a) an implicit observation, (b) a centroid of observations (c) Markov random field (MRF) for observation to track assignment.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133539108","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}
{"title":"Fuzzy based chip level based receiver for direct sequence-code division multiple access communication system","authors":"S. Panda, S. K. Patra","doi":"10.1109/SPCOM.2004.1458375","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458375","url":null,"abstract":"This paper investigates the problem of chip level based (CLB) receivers for direct sequence code division multiple access (DS-CDMA) communication system. A radial basis function (RBF) receiver provides the optimum receiver performance for this system. We propose a fuzzy implementation of the RBF receiver. This fuzzy receiver provides considerable computational complexity reduction with respect to RBF receivers. Additionally this fuzzy receivers has the capability to provide exactly the same performance in terms of bit error rate (BER) as the optimum RBF receiver. Extensive simulation studies validate our finding.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115050338","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}
{"title":"Pronunciation modeling for speech technology","authors":"T. Svendsen","doi":"10.1109/SPCOM.2004.1458347","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458347","url":null,"abstract":"Written text is based on an orthographic representation of words, i.e. linear sequences of letters. Modern speech technology (automatic speech recognition and text-to-speech synthesis) is based on phonetic units representing realization of sounds. A mapping between the orthographic form and phonetic forms representing the pronunciation is thus required. This may be obtained by creating pronunciation lexica and/or rule-based systems for grapheme-to-phoneme conversion. Traditionally, this mapping has been obtained manually, based on phonetic and linguistic knowledge. This approach has a number of drawbacks: i) the pronunciations represent typical pronunciations and will have a limited capacity for describing pronunciation variation due to speaking style and dialectical/accent variations; ii) if multiple pronunciation variants are included, it does not indicate which variants are more significant for the specific application; iii) the description is based on phonetic-knowledge and does not take into account that the units used in speech technology may deviate from the phonetic interpretation; and iv) the description is limited to units with a linguistic interpretation. The paper will present and discuss methods for modeling pronunciation and pronunciation variation specifically for applications in speech technology.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124602462","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}
{"title":"Genetic algorithm based MVDR beam formation for adaptive nulling","authors":"G. Kannan, S. Merchant, U. Desai","doi":"10.1109/SPCOM.2004.1458391","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458391","url":null,"abstract":"Minimum variance distortionless response (MVDR) beam former is a spectral estimation technique where the power of signal in desired direction is maintained and the variance (power) in unwanted direction is minimized. MVDR beam former is generally used in adaptive arrays for adaptive nulling of jammer/interference. Generally in adaptive arrays QR decomposition is used for least square minimization of error, as it has less computational complexity and very fast convergence rate, In this paper we propose, the application of genetic algorithm concepts for (GA) for least square minimization in adaptive arrays. We show that the proposed algorithm is very efficient computationally compared to other algorithms available. The proposed algorithm based only on binary operations.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130019237","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}
{"title":"Time-scaling of speech and music using independent subspace analysis","authors":"R. Muralishankar, L. Kaushik, A. Ramakrishnan","doi":"10.1109/SPCOM.2004.1458408","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458408","url":null,"abstract":"We propose a new technique for modifying the time-scale of speech and music using independent subspace analysis (ISA). To carry out ISA, the single channel mixture signal is converted to a time-frequency representation such as spectrogram. The spectrogram is generated by taking Hartley or wavelet transform on overlapped frames of speech or music. We do dimensionality reduction of the autocorrelated original spectrogram using singular value decomposition. Then, we use independent component analysis to get unmixing matrix using JadeICA algorithm. It is then assumed that the overall spectrogram results from the superposition of a number of unknown statistically independent spectrograms. By using unmixing matrix, independent sources such as temporal amplitude envelopes and frequency weights can be extracted from the spectrogram. Time-scaling of speech and music is carried out by resampling the independent temporal amplitude envelopes. We then multiply the independent frequency weights with time-scaled temporal amplitude envelopes. We Sum these independent spectrograms and take inverse Hartley or wavelet transform of the sum spectrogram. The reconstructed time-domain signal is overlap-added to get the time-scaled signal. The quality of the time-scaled speech and music has been analyzed using Modified Bark spectral distortion (MBSD). From the MBSD score, one can infer that the time-scaled signal is less distorted.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121318249","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}
{"title":"A new transform for 2-D signal representation (MRT) and some of its properties","authors":"R. Roy, R. Gopikakumari","doi":"10.1109/SPCOM.2004.1458423","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458423","url":null,"abstract":"A new transform (MRT) for two-dimensional signal representation and some of its properties are proposed in this paper. The transform helps to do the frequency domain analysis of two-dimensional signals without any complex operations but in terms of real additions. It is obtained by exploiting the periodicity and symmetry of the exponential term in the discrete Fourier transform (DFT) relation, and by grouping related data. Forward and inverse relations of the transform are presented. The transform coefficients show useful redundancies among themselves. These redundancies, which can be used to implement the transform, are studied. A few properties of the transform are studied and the relevant relations are presented.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122537753","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}
{"title":"A new state augmentation for maneuvering targets detection","authors":"H. Khaloozadeh, A. Karsaz","doi":"10.1109/SPCOM.2004.1458358","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458358","url":null,"abstract":"In this paper, an innovation model is presented to transform the maneuvering target tracking problems to the standard Bayesian model, therefore a standard Kalman filter can be applied to them. The modeling is based on mixed Bayesian-fisher uncertainties and a special augmentation in state space. In this model, target position and velocity are conventional states and the acceleration is treated as an additive input term, which has been augmented in the corresponding state equation. The results have been compared with the work of Wang, TC et al., (1993). The simulation results show a high performance of the proposed innovation model and effectiveness of this scheme in tracking maneuvering targets.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123051144","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}
{"title":"A comparison between Alamouti and SVD scheme for OFDM based WLAN system","authors":"P. Hernandis, P. Corral, A. C. de Castro Lima","doi":"10.1109/SPCOM.2004.1458489","DOIUrl":"https://doi.org/10.1109/SPCOM.2004.1458489","url":null,"abstract":"In this paper, we describe a multiple-input-multiple-output (MIMO) wireless system with two transmit and two receive antennas. We compare two different schemes. The first model is based on the space-time block coding known as Alamouti scheme, that simplifies the receiver structure. The second model is singular value decomposition. The proposed system has been implemented in order to study how MIMO provides much better results (in terms of BER and PER) than SISO or MISO systems.","PeriodicalId":424981,"journal":{"name":"2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114183729","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}