Signal synthesis using time-frequency distributions can be improved using an antenna array receiver. The availability of the source signals at different array elements allows the implementation of time-frequency synthesis techniques that utilize the source spatial signatures for crossterm reduction and noise mitigation. We introduce a new technique for signal synthesis based on array averaging of Wigner distributions. The source temporal waveforms are first synthesized and then used to estimate the source spatial signatures. An iterative process incorporating the source signal vector and array vector can be applied until the desired results are reached.
{"title":"Spatial and time-frequency signature estimation of nonstationary sources","authors":"M. Amin, W. Mu, Yimin D. Zhang","doi":"10.1109/SSP.2001.955285","DOIUrl":"https://doi.org/10.1109/SSP.2001.955285","url":null,"abstract":"Signal synthesis using time-frequency distributions can be improved using an antenna array receiver. The availability of the source signals at different array elements allows the implementation of time-frequency synthesis techniques that utilize the source spatial signatures for crossterm reduction and noise mitigation. We introduce a new technique for signal synthesis based on array averaging of Wigner distributions. The source temporal waveforms are first synthesized and then used to estimate the source spatial signatures. An iterative process incorporating the source signal vector and array vector can be applied until the desired results are reached.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"140 1","pages":"313-316"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73277421","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}
Recursive and efficient estimation of polynomial-phase is considered here, with alternatives to the standard Gauss-Newton approach presented. We consider approximations of the likelihood and phase noise distribution to derive recursive approximate maximum likelihood and Bayesian estimators. Monte Carlo simulations indicate that these methods compare favourably with the Gauss-Newton scheme both in terms of computational expense and efficiency thresholds.
{"title":"Computationally efficient iterative refinement techniques for polynomial phase signals","authors":"S. Sando, D. Huang, T. Pettitt","doi":"10.1109/SSP.2001.955312","DOIUrl":"https://doi.org/10.1109/SSP.2001.955312","url":null,"abstract":"Recursive and efficient estimation of polynomial-phase is considered here, with alternatives to the standard Gauss-Newton approach presented. We consider approximations of the likelihood and phase noise distribution to derive recursive approximate maximum likelihood and Bayesian estimators. Monte Carlo simulations indicate that these methods compare favourably with the Gauss-Newton scheme both in terms of computational expense and efficiency thresholds.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"100 1","pages":"421-424"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76367457","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}
A new Markov chain based algorithm for drawing samples from a desired distribution has been proposed. This algorithm, also known as the perfect sampling algorithm, can determine exactly when a Markov chain enters the equilibrium, and hence can output exact samples. We introduce a perfect sampling algorithm called the rejection Gibbs coupler for perfect sampling from bounded multivariate distributions. We demonstrate an application of the rejection coupler for generation of samples from truncated multivariate Gaussian distributions.
{"title":"The rejection Gibbs coupler: A perfect sampling algorithm and its application to truncated multivariate Gaussian distributions","authors":"Yufei Huang, T. Ghirmai, P. Djurić","doi":"10.1109/SSP.2001.955217","DOIUrl":"https://doi.org/10.1109/SSP.2001.955217","url":null,"abstract":"A new Markov chain based algorithm for drawing samples from a desired distribution has been proposed. This algorithm, also known as the perfect sampling algorithm, can determine exactly when a Markov chain enters the equilibrium, and hence can output exact samples. We introduce a perfect sampling algorithm called the rejection Gibbs coupler for perfect sampling from bounded multivariate distributions. We demonstrate an application of the rejection coupler for generation of samples from truncated multivariate Gaussian distributions.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"50 1","pages":"42-45"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87574583","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}
EEG-based brain maps are very useful in anatomical, functional and pathological diagnosis. These images are projections of the energy of the signals in four different frequency bands. Joint approximate diagonalization of eigenmatrices (JADE) is used as an effective tool in the deconvolution of EEG signals prior to spectrum estimation. The algorithm also, restores the noise from the signal as a result of higher order statistics (HOS) estimation. The spectrum is estimated using autoregressive (AR) modelling and pseudo-hot colours are used to represent brain activities. The results show a great enhancement in diagnostic features in the reconstructed images. The overall system also enables real-time reconstruction of the images for patient monitoring purposes.
{"title":"EEG brain map reconstruction using blind source separation","authors":"S. Sanei, A. R. Leyman","doi":"10.1109/SSP.2001.955265","DOIUrl":"https://doi.org/10.1109/SSP.2001.955265","url":null,"abstract":"EEG-based brain maps are very useful in anatomical, functional and pathological diagnosis. These images are projections of the energy of the signals in four different frequency bands. Joint approximate diagonalization of eigenmatrices (JADE) is used as an effective tool in the deconvolution of EEG signals prior to spectrum estimation. The algorithm also, restores the noise from the signal as a result of higher order statistics (HOS) estimation. The spectrum is estimated using autoregressive (AR) modelling and pseudo-hot colours are used to represent brain activities. The results show a great enhancement in diagnostic features in the reconstructed images. The overall system also enables real-time reconstruction of the images for patient monitoring purposes.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"97 1","pages":"233-236"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72950659","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}
Communication networks have to rely on efficient resource allocation schemes to share the network resources (bandwidth, buffer size, etc.) among users offering different types of traffic (eg, voice, video and data). Existing schemes based on self-similar traffic models assume that the network traffic is Gaussian and exhibits long-term memory characteristics only. Certain classes of network traffic (eg, MPEG video traces) are however, non-Gaussian and long-range-dependent. In such cases, resource allocation based on simplified assumptions will be either excessive or fail to provide the specified guarantees on the quality of service (QoS). In an earlier work, we had presented an efficient resource allocation scheme for traffic sources having: (i) Gaussian as well as non-Gaussian (log-normal) distributions; and (ii) exhibiting short-term and/or long-term memory characteristics. In this paper, we assess the real-time performance of our as well as several existing schemes using a Texas Instruments TMS320C6701 DSP. The results show that: (i) although our algorithm has a higher computational load, real-time implementation is still feasible; and (ii) the increased computational load is justified since the proposed algorithm is more reliable in providing QoS guarantees than existing simplified schemes.
{"title":"Self-similar traffic sources: modeling and real-time resource allocation","authors":"K. Nagarajan, G.T. Zhou","doi":"10.1109/SSP.2001.955225","DOIUrl":"https://doi.org/10.1109/SSP.2001.955225","url":null,"abstract":"Communication networks have to rely on efficient resource allocation schemes to share the network resources (bandwidth, buffer size, etc.) among users offering different types of traffic (eg, voice, video and data). Existing schemes based on self-similar traffic models assume that the network traffic is Gaussian and exhibits long-term memory characteristics only. Certain classes of network traffic (eg, MPEG video traces) are however, non-Gaussian and long-range-dependent. In such cases, resource allocation based on simplified assumptions will be either excessive or fail to provide the specified guarantees on the quality of service (QoS). In an earlier work, we had presented an efficient resource allocation scheme for traffic sources having: (i) Gaussian as well as non-Gaussian (log-normal) distributions; and (ii) exhibiting short-term and/or long-term memory characteristics. In this paper, we assess the real-time performance of our as well as several existing schemes using a Texas Instruments TMS320C6701 DSP. The results show that: (i) although our algorithm has a higher computational load, real-time implementation is still feasible; and (ii) the increased computational load is justified since the proposed algorithm is more reliable in providing QoS guarantees than existing simplified schemes.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"29 1","pages":"74-77"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76677348","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}
An efficient algorithm for estimating the peak position of a sampled function is presented. The algorithm uses the Hilbert transform of the function for peak detection via interpolation. The accuracy of the proposed method is demonstrated using an example where the frequency of a sinusoid is determined by detecting the peak of the FFT of the signal. It is shown that the algorithm has computational advantage when the positions of many peaks of the sampled function are required to be estimated, e.g. as in the fundamental and harmonic frequency estimation of an audio signal. Spectral characteristics of the Hilbert transform amplitude and phase functions and the rationale for the use of Hilbert transform for interpolation are also discussed in detail.
{"title":"An efficient Hilbert transform interpolation algorithm for peak position estimation","authors":"S. S. Abeysekera","doi":"10.1109/SSP.2001.955311","DOIUrl":"https://doi.org/10.1109/SSP.2001.955311","url":null,"abstract":"An efficient algorithm for estimating the peak position of a sampled function is presented. The algorithm uses the Hilbert transform of the function for peak detection via interpolation. The accuracy of the proposed method is demonstrated using an example where the frequency of a sinusoid is determined by detecting the peak of the FFT of the signal. It is shown that the algorithm has computational advantage when the positions of many peaks of the sampled function are required to be estimated, e.g. as in the fundamental and harmonic frequency estimation of an audio signal. Spectral characteristics of the Hilbert transform amplitude and phase functions and the rationale for the use of Hilbert transform for interpolation are also discussed in detail.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"33 1","pages":"417-420"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76896983","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}
Mobile radio communication systems are generally designed without taking into account the relative emitter/receiver dynamics. In this paper we model this dynamics as a vector Markov process and formulate ranging and digital demodulation/detection as aspects of recursive absolute (not modulo 2/spl pi/) phase estimation. Symbol-by-symbol detection and phase tracking within symbol interval are performed by a bank of 'matched' stochastic nonlinear estimators and a maximum a posteriori (MAP) decision algorithm. The approach applies to precision landing and communication with low Earth orbit (LEO) satellites or between rapid maneuvering platforms.
{"title":"Recursive Bayesian phase estimation in ranging and mobile communication","authors":"J. Leitao, F. Sousa","doi":"10.1109/SSP.2001.955257","DOIUrl":"https://doi.org/10.1109/SSP.2001.955257","url":null,"abstract":"Mobile radio communication systems are generally designed without taking into account the relative emitter/receiver dynamics. In this paper we model this dynamics as a vector Markov process and formulate ranging and digital demodulation/detection as aspects of recursive absolute (not modulo 2/spl pi/) phase estimation. Symbol-by-symbol detection and phase tracking within symbol interval are performed by a bank of 'matched' stochastic nonlinear estimators and a maximum a posteriori (MAP) decision algorithm. The approach applies to precision landing and communication with low Earth orbit (LEO) satellites or between rapid maneuvering platforms.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"16 1","pages":"202-205"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82982782","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}
We address the problem of channel fading in communication systems. In particular, we focus on the flat fading phenomenon. We study some time-frequency based techniques for the detection of frequency modulated signals subjected to flat fading channels. A comparison, based on the bit error rate, of these techniques is also presented.
{"title":"A study of time-frequency based detectors for FSK modulated signals in a flat fading channel","authors":"B. Barkat, S. Attallah","doi":"10.1109/SSP.2001.955258","DOIUrl":"https://doi.org/10.1109/SSP.2001.955258","url":null,"abstract":"We address the problem of channel fading in communication systems. In particular, we focus on the flat fading phenomenon. We study some time-frequency based techniques for the detection of frequency modulated signals subjected to flat fading channels. A comparison, based on the bit error rate, of these techniques is also presented.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"4 1","pages":"206-209"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87982409","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}
Summary form only given. Linear precoding (LP) is a useful signal processing tool for coping with frequency-selective propagation channels encountered with high-rate wireless block transmissions. LP is important for single- and multi-carrier (OFDM) systems, and has links with error-control coding. It has features for both point-to-point and multiple access links, with emphasis placed on the generalized multicarrier CDMA. Novel ideas of block-spreading and chip-interleaving are also of interest.
{"title":"On the role of linear precoding in signal processing for wireless","authors":"G. Giannakis","doi":"10.1109/SSP.2001.955209","DOIUrl":"https://doi.org/10.1109/SSP.2001.955209","url":null,"abstract":"Summary form only given. Linear precoding (LP) is a useful signal processing tool for coping with frequency-selective propagation channels encountered with high-rate wireless block transmissions. LP is important for single- and multi-carrier (OFDM) systems, and has links with error-control coding. It has features for both point-to-point and multiple access links, with emphasis placed on the generalized multicarrier CDMA. Novel ideas of block-spreading and chip-interleaving are also of interest.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"1 1","pages":"13-"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90266573","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}
Model selection and system identification for cases where the model is required to have both characteristics of time-variance and nonlinearity is considered. To enable identification from a single input/output observation record, the time-variation is approximated by a weighted sum of orthogonal sequences. Wavelet packets are chosen for these sequences and an adapted basis for each time-varying coefficient is selected via the best basis algorithm. Individual wavelet packets are then selected via a multiple hypothesis test which determines those packets that are significant to each approximation, and which may be discarded from the model.
{"title":"Time-varying quadratic model selection using wavelet packets","authors":"M. Green","doi":"10.1109/SSP.2001.955293","DOIUrl":"https://doi.org/10.1109/SSP.2001.955293","url":null,"abstract":"Model selection and system identification for cases where the model is required to have both characteristics of time-variance and nonlinearity is considered. To enable identification from a single input/output observation record, the time-variation is approximated by a weighted sum of orthogonal sequences. Wavelet packets are chosen for these sequences and an adapted basis for each time-varying coefficient is selected via the best basis algorithm. Individual wavelet packets are then selected via a multiple hypothesis test which determines those packets that are significant to each approximation, and which may be discarded from the model.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"5 1","pages":"345-348"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90477190","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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