Pub Date : 2000-10-29DOI: 10.1109/ACSSC.2000.910987
H. Witzgall, A. Tarr, J. S. Goldstein
The ROCKET (reduced order correlation kernel estimation technique) algorithm is a new reduced rank autoregressive (AR) spectrum estimation technique which is substantially more robust to signal rank underestimation and significantly more computationally efficient then conventional reduced rank techniques based on principal component analysis. Perhaps more importantly, ROCKET's reduce rank performance has the potential to surpass the performance of full rank AR spectrum estimation techniques. ROCKET is based on the observation that the reduced rank subspace of importance is the one that best predicts the desired signal from the data. ROCKET's subspace is formed in an iterative manner from the cross-correlation vectors defined by a specified desired signal and data. Projecting the desired signal onto this new subspace allows for a significantly reduced dimensional weight vector with the aforementioned properties and benefits.
{"title":"ROCKET: a reduced order correlation kernel estimation technique","authors":"H. Witzgall, A. Tarr, J. S. Goldstein","doi":"10.1109/ACSSC.2000.910987","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.910987","url":null,"abstract":"The ROCKET (reduced order correlation kernel estimation technique) algorithm is a new reduced rank autoregressive (AR) spectrum estimation technique which is substantially more robust to signal rank underestimation and significantly more computationally efficient then conventional reduced rank techniques based on principal component analysis. Perhaps more importantly, ROCKET's reduce rank performance has the potential to surpass the performance of full rank AR spectrum estimation techniques. ROCKET is based on the observation that the reduced rank subspace of importance is the one that best predicts the desired signal from the data. ROCKET's subspace is formed in an iterative manner from the cross-correlation vectors defined by a specified desired signal and data. Projecting the desired signal onto this new subspace allows for a significantly reduced dimensional weight vector with the aforementioned properties and benefits.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"116 1","pages":"406-410 vol.1"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79622171","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 : 2000-10-29DOI: 10.1109/ACSSC.2000.911056
S. Mudulodu, A. Paulraj
There has been a growing interest in the use of multiple transmit and receive antennas for wireless communications, due to the enormous increase in data rate that they promise over single antenna systems. Spatial multiplexing is a scheme that aims to achieve such high data rates by transmitting an independent substream of data from each transmit antenna. However when the receive spatial signatures are poor (i.e., when the channel is not favorable), one or more transmit antennas can not be used to transmit an independent stream. In fixed modulation systems this results in some loss in data rate. We consider such fixed modulation systems and propose a scheme that uses multiple spreading codes as in CDMA MIMO (multiple input multiple output) systems to smartly combine code multiplexing with spatial multiplexing in order to mitigate this loss in data rate. We also show that, in the presence of a low bandwidth feedback path, the proposed scheme, unlike the spatial-only multiplexing scheme, allows the transmitter to adapt the data, rate smoothly based on the receive spatial signatures.
{"title":"A simple multiplexing scheme for MIMO systems using multiple spreading codes","authors":"S. Mudulodu, A. Paulraj","doi":"10.1109/ACSSC.2000.911056","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.911056","url":null,"abstract":"There has been a growing interest in the use of multiple transmit and receive antennas for wireless communications, due to the enormous increase in data rate that they promise over single antenna systems. Spatial multiplexing is a scheme that aims to achieve such high data rates by transmitting an independent substream of data from each transmit antenna. However when the receive spatial signatures are poor (i.e., when the channel is not favorable), one or more transmit antennas can not be used to transmit an independent stream. In fixed modulation systems this results in some loss in data rate. We consider such fixed modulation systems and propose a scheme that uses multiple spreading codes as in CDMA MIMO (multiple input multiple output) systems to smartly combine code multiplexing with spatial multiplexing in order to mitigate this loss in data rate. We also show that, in the presence of a low bandwidth feedback path, the proposed scheme, unlike the spatial-only multiplexing scheme, allows the transmitter to adapt the data, rate smoothly based on the receive spatial signatures.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"44 1","pages":"769-774 vol.1"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81332122","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 : 2000-10-29DOI: 10.1109/ACSSC.2000.910649
G. Fan, X. Xia
Wavelet-domain hidden Markov models (HMMs), in particular the hidden Markov tree (HMT), have been proposed and applied to image processing, e.g. denoising and segmentation. In this paper texture analysis and classification using wavelet-domain HMMs are studied. In order to achieve more accurate texture characterization, we propose a new tree-structured HMM, called the 2-D HMT-3, where the wavelet coefficients from three subbands are grouped together. Besides the interscale dependencies, the proposed 2-D HMT-3 can also capture the dependencies across the wavelet subbands that are found useful for texture analysis. The experimental results show that the 2-D HMT-3 provides a nearly 20% improvement over the method using wavelet energy signatures, and the overall percentage of correct classification is over 95% upon a set of 55 Brodatz (1966) textures.
{"title":"Maximum likelihood texture analysis and classification using wavelet-domain hidden Markov models","authors":"G. Fan, X. Xia","doi":"10.1109/ACSSC.2000.910649","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.910649","url":null,"abstract":"Wavelet-domain hidden Markov models (HMMs), in particular the hidden Markov tree (HMT), have been proposed and applied to image processing, e.g. denoising and segmentation. In this paper texture analysis and classification using wavelet-domain HMMs are studied. In order to achieve more accurate texture characterization, we propose a new tree-structured HMM, called the 2-D HMT-3, where the wavelet coefficients from three subbands are grouped together. Besides the interscale dependencies, the proposed 2-D HMT-3 can also capture the dependencies across the wavelet subbands that are found useful for texture analysis. The experimental results show that the 2-D HMT-3 provides a nearly 20% improvement over the method using wavelet energy signatures, and the overall percentage of correct classification is over 95% upon a set of 55 Brodatz (1966) textures.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"1 1","pages":"921-925 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82874433","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 : 2000-10-29DOI: 10.1109/ACSSC.2000.911001
A. Tsai, A. Yezzi, A. Willsky
We first address the problem of simultaneous image segmentation and smoothing by approaching the Mumford-Shah (1989) paradigm from a curve evolution perspective. In particular we let a set of deformable contours define the boundaries between regions in an image where we model the data via piecewise smooth functions and employ a gradient flow to evolve these contours. Next, we generalize the data fidelity term of the original Mumford-Shah functional to incorporate a spatially varying penalty. This more general model leads us to a novel partial differential equation (PDE) based approach for simultaneous image magnification, segmentation, and smoothing.
{"title":"A PDE approach to image smoothing and magnification using the Mumford-Shah functional","authors":"A. Tsai, A. Yezzi, A. Willsky","doi":"10.1109/ACSSC.2000.911001","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.911001","url":null,"abstract":"We first address the problem of simultaneous image segmentation and smoothing by approaching the Mumford-Shah (1989) paradigm from a curve evolution perspective. In particular we let a set of deformable contours define the boundaries between regions in an image where we model the data via piecewise smooth functions and employ a gradient flow to evolve these contours. Next, we generalize the data fidelity term of the original Mumford-Shah functional to incorporate a spatially varying penalty. This more general model leads us to a novel partial differential equation (PDE) based approach for simultaneous image magnification, segmentation, and smoothing.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"24 1","pages":"473-477 vol.1"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88848141","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 : 2000-10-29DOI: 10.1109/ACSSC.2000.911247
D. Garren, M. K. Osborn, A. C. Odom, J. S. Goldstein, S. Unnikrishna Pillai, J. Guerci
This paper investigates the optimization of a single transmit pulse shape and the receiver response to maximize either target detection or identity discrimination between two structurally similar ground mobile targets: the T-72 and M1 main battle tanks. This theory incorporates effects due to the uncertainty in the prior knowledge of the target aspect relative to the sensor. The improvement in the signal-to-interference-plus-noise (SINR) resulting from the optimized transmit pulse shape over that of a standard chirped waveform typically lies between 4 dB and 9 dB. Similar improvements in target identification performance are also obtained.
{"title":"Optimization of single transmit pulse shape to maximize detection and identification of ground mobile targets","authors":"D. Garren, M. K. Osborn, A. C. Odom, J. S. Goldstein, S. Unnikrishna Pillai, J. Guerci","doi":"10.1109/ACSSC.2000.911247","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.911247","url":null,"abstract":"This paper investigates the optimization of a single transmit pulse shape and the receiver response to maximize either target detection or identity discrimination between two structurally similar ground mobile targets: the T-72 and M1 main battle tanks. This theory incorporates effects due to the uncertainty in the prior knowledge of the target aspect relative to the sensor. The improvement in the signal-to-interference-plus-noise (SINR) resulting from the optimized transmit pulse shape over that of a standard chirped waveform typically lies between 4 dB and 9 dB. Similar improvements in target identification performance are also obtained.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"29 1","pages":"1535-1539 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89300302","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 : 2000-10-29DOI: 10.1109/ACSSC.2000.910924
G. Mandyam
Previous work in mobile wireless communications systems has centered on the use of closed-loop transmit diversity to increase performance in fading channels. Closed-loop transmit diversity methods, which employ feedback of optimal weighting vectors so as to pre-weight transmitted symbols from multiple antennas, suffer from two problems: (1) degradation at high mobile velocities due to limited-rate feedback, and (2) increasing feedback information rate with increasing number of transmit antennas. A method of closed-loop transmit diversity which addresses both of the problems listed above is presented based on the use of unitary transformations for transmitter diversity.
{"title":"Application of unitary transforms to quasi-closed-loop transmit diversity systems","authors":"G. Mandyam","doi":"10.1109/ACSSC.2000.910924","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.910924","url":null,"abstract":"Previous work in mobile wireless communications systems has centered on the use of closed-loop transmit diversity to increase performance in fading channels. Closed-loop transmit diversity methods, which employ feedback of optimal weighting vectors so as to pre-weight transmitted symbols from multiple antennas, suffer from two problems: (1) degradation at high mobile velocities due to limited-rate feedback, and (2) increasing feedback information rate with increasing number of transmit antennas. A method of closed-loop transmit diversity which addresses both of the problems listed above is presented based on the use of unitary transformations for transmitter diversity.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"82 1","pages":"97-101 vol.1"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89018857","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 : 2000-10-29DOI: 10.1109/ACSSC.2000.911017
M. Koca, B. Levy
For pt.I see ibid., p.552-56 (2000). This paper presents a turbo equalization method for complex TCM signals over frequency selective, multipath fading channels based on receiver antenna array measurements. The channel observed at each array element is described as an equivalent convolutional encoder acting on the interleaved TCM symbols. The received vector signal can be viewed as produced by a serial concatenated encoder and is decoded by an iterative equalizer that employs M-ary soft output Viterbi algorithm (SOVA) as the decoding rule. Since the computational complexity of the equalizer increases with the number of ISI symbols and antennas used in the receiver, an alternative receiver is also considered where the array outputs are first combined through a beamformer and then sent to the equalizer. Both receiver structures are simulated for two dimensional TCM signals such as 8-16 PSK and 16-QAM and the results indicate an improved performance of the diversity receiver.
{"title":"Turbo space-time equalization of TCM with receiver diversity .II. Maximum-likelihood detection","authors":"M. Koca, B. Levy","doi":"10.1109/ACSSC.2000.911017","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.911017","url":null,"abstract":"For pt.I see ibid., p.552-56 (2000). This paper presents a turbo equalization method for complex TCM signals over frequency selective, multipath fading channels based on receiver antenna array measurements. The channel observed at each array element is described as an equivalent convolutional encoder acting on the interleaved TCM symbols. The received vector signal can be viewed as produced by a serial concatenated encoder and is decoded by an iterative equalizer that employs M-ary soft output Viterbi algorithm (SOVA) as the decoding rule. Since the computational complexity of the equalizer increases with the number of ISI symbols and antennas used in the receiver, an alternative receiver is also considered where the array outputs are first combined through a beamformer and then sent to the equalizer. Both receiver structures are simulated for two dimensional TCM signals such as 8-16 PSK and 16-QAM and the results indicate an improved performance of the diversity receiver.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"116 1","pages":"557-561 vol.1"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89412040","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 : 2000-10-29DOI: 10.1109/ACSSC.2000.911282
A. Sharma, R. Moses
We investigate the use of subspace-based detectors for discriminating vehicles from trees in low frequency synthetic aperture imagery. We model tree scattering as structured isotropic interference responses and model dominant vehicle scattering as dihedral responses. We form linear subspaces of tree and target responses, and apply subspace-based detection methods developed by Scharf and Friedlander (1994). Analysis on synthetic tree and target models show the viability of this approach. Preliminary results on measured imagery provide lower performance, suggesting the need for improved data calibration and improved scattering models of trees at low frequencies.
{"title":"Matched subspace detectors for discrimination of targets from trees in SAR imagery","authors":"A. Sharma, R. Moses","doi":"10.1109/ACSSC.2000.911282","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.911282","url":null,"abstract":"We investigate the use of subspace-based detectors for discriminating vehicles from trees in low frequency synthetic aperture imagery. We model tree scattering as structured isotropic interference responses and model dominant vehicle scattering as dihedral responses. We form linear subspaces of tree and target responses, and apply subspace-based detection methods developed by Scharf and Friedlander (1994). Analysis on synthetic tree and target models show the viability of this approach. Preliminary results on measured imagery provide lower performance, suggesting the need for improved data calibration and improved scattering models of trees at low frequencies.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"16 1","pages":"1721-1726 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88939774","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 : 2000-10-29DOI: 10.1109/ACSSC.2000.910974
P. Shen, C. Lindquist
Adaptive filtering allows noisy signals to be analyzed. This paper examines different types of adaptive estimation filters for EKG signals having little a priori information.
自适应滤波允许分析噪声信号。本文研究了不同类型的自适应估计滤波器对缺乏先验信息的心电信号的影响。
{"title":"Adaptive filtering of EKG signals with little a priori information","authors":"P. Shen, C. Lindquist","doi":"10.1109/ACSSC.2000.910974","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.910974","url":null,"abstract":"Adaptive filtering allows noisy signals to be analyzed. This paper examines different types of adaptive estimation filters for EKG signals having little a priori information.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"15 1","pages":"338-342 vol.1"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88988457","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 : 2000-10-29DOI: 10.1109/ACSSC.2000.910688
M. Rangaswamy, B. Himed, J. Michels
We consider the statistical analysis of the recently proposed nonhomogeneity detector for Gaussian interference statistics. We show that a more stringent test can be constructed by accounting for the statistics of the generalized inner product (GIP) test under the condition of finite training data support. In particular, exact theoretical expressions for the GIP probability density function (PDF) and GIP mean are derived. Additionally, we show that for Gaussian interference statistics, the GIP admits a simple representation as the ratio of two statistically independent chi-square distributed random variables. Performance analysis of the more stringent GIP based test is presented.
{"title":"Statistical analysis of the nonhomogeneity detector","authors":"M. Rangaswamy, B. Himed, J. Michels","doi":"10.1109/ACSSC.2000.910688","DOIUrl":"https://doi.org/10.1109/ACSSC.2000.910688","url":null,"abstract":"We consider the statistical analysis of the recently proposed nonhomogeneity detector for Gaussian interference statistics. We show that a more stringent test can be constructed by accounting for the statistics of the generalized inner product (GIP) test under the condition of finite training data support. In particular, exact theoretical expressions for the GIP probability density function (PDF) and GIP mean are derived. Additionally, we show that for Gaussian interference statistics, the GIP admits a simple representation as the ratio of two statistically independent chi-square distributed random variables. Performance analysis of the more stringent GIP based test is presented.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"12 4 1","pages":"1117-1121 vol.2"},"PeriodicalIF":0.0,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90232315","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：