Pub Date : 1998-10-06DOI: 10.1109/TFSA.1998.721443
J.-P.G. Gallaire, A. Sayeed
The difficulty of modeling interference is one of the main problems in constructing an efficient interference-resistant detector. We present a new detector which exploits the signal correlation structure to account for interference. In order to make a decision between two composite hypotheses, our detector uses the generalized likelihood ratio test. Preliminary results suggest that the resulting detection scheme achieves high performance in presence of strong interference.
{"title":"Interference-resistant detection based on time-frequency subspaces","authors":"J.-P.G. Gallaire, A. Sayeed","doi":"10.1109/TFSA.1998.721443","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721443","url":null,"abstract":"The difficulty of modeling interference is one of the main problems in constructing an efficient interference-resistant detector. We present a new detector which exploits the signal correlation structure to account for interference. In order to make a decision between two composite hypotheses, our detector uses the generalized likelihood ratio test. Preliminary results suggest that the resulting detection scheme achieves high performance in presence of strong interference.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115294014","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 : 1998-10-06DOI: 10.1109/TFSA.1998.721403
S. Velazquez
The advanced filter bank analog-to-digital converter (AFB ADC) is a breakthrough approach to very high-speed, high-resolution analog-to-digital conversion which improves the speed of conversion by up to six times the state-of-the-art by using a parallel array of individual converters (patent pending). The AFB ADC uses multirate filter bank signal processing to improve performance. Because of its unique architecture, the AFB ADC is continuously upgradeable as new analog-to-digital converter chips become available, thereby maintaining its performance advantage. This paper describes the architecture and provides hardware prototype results for a 12-bit, 80 MSa/s system for use in a universal, software-reconfigurable radio frequency (RF) receiver for cellular, satellite, or military communications. A 14-bit, 325 MSa/s system is currently being developed.
{"title":"High-performance advanced filter bank analog-to-digital converter for universal RF receivers","authors":"S. Velazquez","doi":"10.1109/TFSA.1998.721403","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721403","url":null,"abstract":"The advanced filter bank analog-to-digital converter (AFB ADC) is a breakthrough approach to very high-speed, high-resolution analog-to-digital conversion which improves the speed of conversion by up to six times the state-of-the-art by using a parallel array of individual converters (patent pending). The AFB ADC uses multirate filter bank signal processing to improve performance. Because of its unique architecture, the AFB ADC is continuously upgradeable as new analog-to-digital converter chips become available, thereby maintaining its performance advantage. This paper describes the architecture and provides hardware prototype results for a 12-bit, 80 MSa/s system for use in a universal, software-reconfigurable radio frequency (RF) receiver for cellular, satellite, or military communications. A 14-bit, 325 MSa/s system is currently being developed.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127267875","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 : 1998-10-06DOI: 10.1109/TFSA.1998.721353
B. Iem, A. Papandreou-Suppappola, G. Boudreaux-Bartels
We extend the work of Shenoy and Parks (1994) on the wideband Weyl correspondence. We define a wideband Weyl symbol (P/sub 0/WS) in the time-frequency plane based on the Bertrand (1988) P/sub 0/-distribution, and we study its properties, examples and possible applications. Using warping relations, we generalize the P/sub 0/WS and the wideband spreading function (WSF) to analyze systems producing dispersive time shifts. We provide properties and special cases (e.g. power and exponential) to demonstrate the importance of our generalization. The new generalized WSF provides a new interpretation of a system output as a weighted superposition of dispersive time-shifted versions of the signal. We provide application examples in analysis and detection to demonstrate the advantages of our new results for linear systems with group delay characteristics matched to the specific warping used.
{"title":"A wideband time-frequency Weyl symbol and its generalization","authors":"B. Iem, A. Papandreou-Suppappola, G. Boudreaux-Bartels","doi":"10.1109/TFSA.1998.721353","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721353","url":null,"abstract":"We extend the work of Shenoy and Parks (1994) on the wideband Weyl correspondence. We define a wideband Weyl symbol (P/sub 0/WS) in the time-frequency plane based on the Bertrand (1988) P/sub 0/-distribution, and we study its properties, examples and possible applications. Using warping relations, we generalize the P/sub 0/WS and the wideband spreading function (WSF) to analyze systems producing dispersive time shifts. We provide properties and special cases (e.g. power and exponential) to demonstrate the importance of our generalization. The new generalized WSF provides a new interpretation of a system output as a weighted superposition of dispersive time-shifted versions of the signal. We provide application examples in analysis and detection to demonstrate the advantages of our new results for linear systems with group delay characteristics matched to the specific warping used.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127444845","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 : 1998-10-06DOI: 10.1109/TFSA.1998.721473
H. Bolcskei, F. Hlawatsch
We introduce a new method for quantization noise reduction in oversampled filter banks. This method is based on predictive quantization and achieves much better noise reduction than the best existing methods for noise reduction in overcomplete representations. It is demonstrated that the proposed oversampled predictive subband coders are well suited for subband coding applications where low resolution quantizers have to be used. In this case, oversampling combined with linear prediction improves the effective resolution of the subband coder at the cost of increased rate. Simulation results are provided to assess the achievable quantization noise reduction and resolution enhancement.
{"title":"Quantization noise reduction in oversampled filter banks","authors":"H. Bolcskei, F. Hlawatsch","doi":"10.1109/TFSA.1998.721473","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721473","url":null,"abstract":"We introduce a new method for quantization noise reduction in oversampled filter banks. This method is based on predictive quantization and achieves much better noise reduction than the best existing methods for noise reduction in overcomplete representations. It is demonstrated that the proposed oversampled predictive subband coders are well suited for subband coding applications where low resolution quantizers have to be used. In this case, oversampling combined with linear prediction improves the effective resolution of the subband coder at the cost of increased rate. Simulation results are provided to assess the achievable quantization noise reduction and resolution enhancement.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122743456","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 : 1998-10-06DOI: 10.1109/TFSA.1998.721378
Jen-Chang Liu, W. Hwang
Fractional Brownian motion (fBm) is a non-stationary stochastic model, which has a 1/f spectrum and statistical self-similar property. We extend the proposed methods of Hwang to an isotropic 2-D noisy fBm image. The extension is not straightforward; although one can obtain the fractal parameter of an isotropic fBm by averaging of the estimated fractal parameters from several directions by means of the 1-D fractal parameter estimation algorithm, this approach does not perform well in practice. It was shown by Hwang that it requires more than 1000 sampled points for a robust 1-D fractal parameter estimation. For a median size image (say with size 256 by 256 or smaller), there is not enough pixels at each direction for a robust 1-D fractal parameter estimation. Thus, alternative methods must be developed in order that the robustness fractal estimation from a noisy fBm image with small size can be achieved. In this paper, we show that the wavelet transform of an isotropic fBm image at each scale is a two-dimensional weakly stationary process at both the horizontal and vertical directions. Thus, robust fractal parameter estimation can be obtained from two-dimensional wavelet coefficients, even for a small noisy fBm image. We propose a fractal parameter estimation algorithm which formulates the robust fractal parameter estimation problem as the characterization of a composite singularity from the autocorrelation of wavelet transforms of a noisy fBm image.
{"title":"Parameter estimation and denoising of 2-D noisy fractional Brownian motion using non-orthogonal wavelets","authors":"Jen-Chang Liu, W. Hwang","doi":"10.1109/TFSA.1998.721378","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721378","url":null,"abstract":"Fractional Brownian motion (fBm) is a non-stationary stochastic model, which has a 1/f spectrum and statistical self-similar property. We extend the proposed methods of Hwang to an isotropic 2-D noisy fBm image. The extension is not straightforward; although one can obtain the fractal parameter of an isotropic fBm by averaging of the estimated fractal parameters from several directions by means of the 1-D fractal parameter estimation algorithm, this approach does not perform well in practice. It was shown by Hwang that it requires more than 1000 sampled points for a robust 1-D fractal parameter estimation. For a median size image (say with size 256 by 256 or smaller), there is not enough pixels at each direction for a robust 1-D fractal parameter estimation. Thus, alternative methods must be developed in order that the robustness fractal estimation from a noisy fBm image with small size can be achieved. In this paper, we show that the wavelet transform of an isotropic fBm image at each scale is a two-dimensional weakly stationary process at both the horizontal and vertical directions. Thus, robust fractal parameter estimation can be obtained from two-dimensional wavelet coefficients, even for a small noisy fBm image. We propose a fractal parameter estimation algorithm which formulates the robust fractal parameter estimation problem as the characterization of a composite singularity from the autocorrelation of wavelet transforms of a noisy fBm image.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122815095","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 : 1998-10-06DOI: 10.1109/TFSA.1998.721503
I. Cohen, S. Raz, D. Malah
A translation-invariant denoising method, based on the minimum description length (MDL) criterion and the shift-invariant wavelet packet decomposition (SIWPD) is presented. A collection of signal models is generated using an extended library of orthonormal wavelet-packet bases, and an additive cost function, approximately representing the MDL principle, is derived. We show that the minimum description length of the noisy observed data is achieved by utilizing the SIWPD and thresholding the resulting coefficients. The signal estimator is combined with a modified Wigner distribution, yielding robust time-frequency representations, characterized by the high resolution and suppressed interference-terms. The proposed method is compared with alternative approaches, and its superiority is demonstrated.
{"title":"MDL-based translation-invariant denoising and robust time-frequency representations","authors":"I. Cohen, S. Raz, D. Malah","doi":"10.1109/TFSA.1998.721503","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721503","url":null,"abstract":"A translation-invariant denoising method, based on the minimum description length (MDL) criterion and the shift-invariant wavelet packet decomposition (SIWPD) is presented. A collection of signal models is generated using an extended library of orthonormal wavelet-packet bases, and an additive cost function, approximately representing the MDL principle, is derived. We show that the minimum description length of the noisy observed data is achieved by utilizing the SIWPD and thresholding the resulting coefficients. The signal estimator is combined with a modified Wigner distribution, yielding robust time-frequency representations, characterized by the high resolution and suppressed interference-terms. The proposed method is compared with alternative approaches, and its superiority is demonstrated.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114607980","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 : 1998-10-06DOI: 10.1109/TFSA.1998.721501
B. Aysin, Luis F. Chaparro, I. Grave, V. Shusterman
We show that denoising a non-stationary signal is possible by means of a Karhunen-Loeve (KL) expansion optimized by an entropy criterion. This criterion is used to segment the noisy signal and to choose the most parsimonious KL representation possible for each segment. The entropy of the KL coefficients for different window lengths determines the appropriate number and the lengths of the windows. To find the KL coefficients in each segment, a time-varying autocorrelation matrix is estimated using the evolutionary periodogram. Eigenvalues and eigenvectors needed in the expansion are computed from this matrix. The local eigenvectors are the basis for each segment. An estimate of the evolutionary spectrum of the signal is obtained from the KL expansion. Choosing the KL coefficients corresponding to the most significant eigenvalues and time-windowing are shown to constitute masking in the time-frequency plane. This masking permits the denoising of non-stationary signals corrupted by white noise.
{"title":"Denoising of non-stationary signals using optimized Karhunen-Loeve expansion","authors":"B. Aysin, Luis F. Chaparro, I. Grave, V. Shusterman","doi":"10.1109/TFSA.1998.721501","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721501","url":null,"abstract":"We show that denoising a non-stationary signal is possible by means of a Karhunen-Loeve (KL) expansion optimized by an entropy criterion. This criterion is used to segment the noisy signal and to choose the most parsimonious KL representation possible for each segment. The entropy of the KL coefficients for different window lengths determines the appropriate number and the lengths of the windows. To find the KL coefficients in each segment, a time-varying autocorrelation matrix is estimated using the evolutionary periodogram. Eigenvalues and eigenvectors needed in the expansion are computed from this matrix. The local eigenvectors are the basis for each segment. An estimate of the evolutionary spectrum of the signal is obtained from the KL expansion. Choosing the KL coefficients corresponding to the most significant eigenvalues and time-windowing are shown to constitute masking in the time-frequency plane. This masking permits the denoising of non-stationary signals corrupted by white noise.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128411948","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 : 1998-10-06DOI: 10.1109/TFSA.1998.721506
J.-P.G. Gallaire, A. Sayeed
Existing denoising schemes rarely use multiple-bases representations and if they do, they do not address the choice of the different bases. We present a new denoising scheme based on multiple bases processing. The multiple bases used in the denoising algorithm are generated via unitary transforms. These unitary transforms also allow the construction of new wavelet bases. In the new domains spanned by the multiple bases, we apply a simple hard thresholding technique as well as a more complex Wiener filtering scheme. Preliminary results suggest that the resulting algorithms can deliver significantly improved performance over the undecimated wavelet transform without being computationally more expensive.
{"title":"Wavelet-based empirical Wiener filtering","authors":"J.-P.G. Gallaire, A. Sayeed","doi":"10.1109/TFSA.1998.721506","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721506","url":null,"abstract":"Existing denoising schemes rarely use multiple-bases representations and if they do, they do not address the choice of the different bases. We present a new denoising scheme based on multiple bases processing. The multiple bases used in the denoising algorithm are generated via unitary transforms. These unitary transforms also allow the construction of new wavelet bases. In the new domains spanned by the multiple bases, we apply a simple hard thresholding technique as well as a more complex Wiener filtering scheme. Preliminary results suggest that the resulting algorithms can deliver significantly improved performance over the undecimated wavelet transform without being computationally more expensive.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129673902","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 : 1998-10-06DOI: 10.1109/TFSA.1998.721481
P. Loughlin, K. Davidson
Time-frequency distribution (TFD) theory suggests that the average frequency at each time and the spread about that average (the instantaneous frequency and bandwidth) are given by the first and second conditional moments in frequency of the TFD of the signal. However, these results are usually obtained from TFDs that are not distributions in the usual sense, and often-times yield peculiar results (e.g., complex-valued instantaneous bandwidth). We explore the conditional or local variances of some common TFDs, and determine for what signal types are the local variances positive. We also examine what bearing the uncertainty principle has on limiting the local resolution of TFDs, in terms of a bound on the local bandwidth-duration product.
{"title":"Positive local variances of time-frequency distributions and local uncertainty","authors":"P. Loughlin, K. Davidson","doi":"10.1109/TFSA.1998.721481","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721481","url":null,"abstract":"Time-frequency distribution (TFD) theory suggests that the average frequency at each time and the spread about that average (the instantaneous frequency and bandwidth) are given by the first and second conditional moments in frequency of the TFD of the signal. However, these results are usually obtained from TFDs that are not distributions in the usual sense, and often-times yield peculiar results (e.g., complex-valued instantaneous bandwidth). We explore the conditional or local variances of some common TFDs, and determine for what signal types are the local variances positive. We also examine what bearing the uncertainty principle has on limiting the local resolution of TFDs, in terms of a bound on the local bandwidth-duration product.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123903794","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 : 1998-10-06DOI: 10.1109/TFSA.1998.721388
M. J. Bastiaans, A. van Leest
The fractional Fourier transformation is used to transform the rectangular Gabor lattice into a quincunx lattice. By using the isometric property of the unitary fractional Fourier transformation, the biorthogonality relation for the rectangular lattice is transformed into a relation which holds for the quincunx lattice. Since a Gaussian function, which plays an important role as a window function in Gabor theory, is an eigenfunction of the fractional Fourier transformation, this transformation has a clear advantage over other operations that are used to transform a rectangular lattice into a quincunx lattice.
{"title":"Rectangular-to-quincunx Gabor lattice conversion via fractional Fourier transformation","authors":"M. J. Bastiaans, A. van Leest","doi":"10.1109/TFSA.1998.721388","DOIUrl":"https://doi.org/10.1109/TFSA.1998.721388","url":null,"abstract":"The fractional Fourier transformation is used to transform the rectangular Gabor lattice into a quincunx lattice. By using the isometric property of the unitary fractional Fourier transformation, the biorthogonality relation for the rectangular lattice is transformed into a relation which holds for the quincunx lattice. Since a Gaussian function, which plays an important role as a window function in Gabor theory, is an eigenfunction of the fractional Fourier transformation, this transformation has a clear advantage over other operations that are used to transform a rectangular lattice into a quincunx lattice.","PeriodicalId":395542,"journal":{"name":"Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126248607","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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