The Experts below are selected from a list of 2232 Experts worldwide ranked by ideXlab platform
Allen Gersho - One of the best experts on this subject based on the ideXlab platform.
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globally optimal vector quantizer design by stochastic relaxation
IEEE Transactions on Signal Processing, 1992Co-Authors: Kenneth Zeger, Jacques Vaisey, Allen GershoAbstract:The authors present a unified formulation and study of vector quantizer design methods that couple stochastic relaxation (SR) techniques with the generalized Lloyd Algorithm. Two new SR techniques are investigated and compared: simulated annealing (SA) and a reduced-complexity approach that modifies the traditional acceptance criterion for simulated annealing to an unconditional acceptance of perturbations. It is shown that four existing techniques all fit into a general methodology for vector quantizer design aimed at finding a globally optimal solution. Comparisons of the Algorithms' performances when quantizing Gauss-Markov processes, speech, and image sources are given. The SA method is guaranteed to perform in a globally optimal manner, and the SR technique gives empirical results equivalent to those of SA. Both techniques result in significantly better performance than that obtained with the generalized Lloyd Algorithm. >
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Globally Optimal Vector Quantizer Design by
1992Co-Authors: Kenneth Zeger, Jacques Vaisey, Allen GershoAbstract:This paper presents a unified formulation and study of vector quantizer design methods that couple stochastic re- laxation (SR) techniques with the generalized Lloyd Algorithm. Two new SR techniques are investigated and compared: simu- lated annealing (SA), and a reduced-complexity approach that modifies the traditional acceptance criterion for simulated an- nealing to an unconditional acceptance of perturbations. It is shown that four existing techniques all fit into a general meth- odology for vector quantizer design aimed at finding a globally optimal solution. Comparisons of each Algorithms' perfor- mance when quantizing Gauss-Markov processes, speech, and image sources are given. The SA method is guaranteed to per- form in a globally optimal manner, and the SR technique gives empirical results equivalent to those of SA. Both techniques re- sult in significantly better performance than that obtained with the generalized Lloyd Algorithm.
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Competitive learning and soft competition for vector quantizer design
IEEE Transactions on Signal Processing, 1992Co-Authors: E. Yair, Kenneth Zeger, Allen GershoAbstract:The authors provide a convergence analysis for the Kohonen learning Algorithm (KLA) with respect to vector quantizer (VQ) optimality criteria and introduce a stochastic relaxation technique which produces the global minimum but is computationally expensive. By incorporating the principles of the stochastic approach into the KLA, a deterministic VQ design Algorithm, the soft competition scheme (SCS), is introduced. Experimental results are presented where the SCS consistently provided better codebooks than the generalized Lloyd Algorithm (GLA), even when the same computation time was used for both Algorithms. The SCS may therefore prove to be a valuable alternative to the GLA for VQ design. >
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ICASSP - A parallel processing Algorithm for vector quantizer design based on subpartitioning
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics Speech and Signal Processing, 1991Co-Authors: Kenneth Zeger, Allen GershoAbstract:A technique for designing vector quantizers that is well suited for parallel processing environments is presented. The input space is iteratively partitioned into M disjoint connected regions composed of unions of partition regions. Each of M processors then independently commutes an optimal subquantizer for its restricted input space. The partitions can regularly be changed to further improve the overall quantizer performance. This technique can improve on the performance of the generalized Lloyd Algorithm by following the traditional design process with the subpartitioning iterations. >
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ICASSP - Conjugate gradient methods for designing vector quantizers
International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: Eyal Yair, Kenneth Zeger, Allen GershoAbstract:A technique for efficient vector quantization (VQ) design based on conjugate-gradient search methods is introduced. It is demonstrated experimentally that the new design Algorithm performs better than the generalized Lloyd Algorithm in many cases in terms of computation time and/or quality of the codebook it produces. >
Kenneth Zeger - One of the best experts on this subject based on the ideXlab platform.
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globally optimal vector quantizer design by stochastic relaxation
IEEE Transactions on Signal Processing, 1992Co-Authors: Kenneth Zeger, Jacques Vaisey, Allen GershoAbstract:The authors present a unified formulation and study of vector quantizer design methods that couple stochastic relaxation (SR) techniques with the generalized Lloyd Algorithm. Two new SR techniques are investigated and compared: simulated annealing (SA) and a reduced-complexity approach that modifies the traditional acceptance criterion for simulated annealing to an unconditional acceptance of perturbations. It is shown that four existing techniques all fit into a general methodology for vector quantizer design aimed at finding a globally optimal solution. Comparisons of the Algorithms' performances when quantizing Gauss-Markov processes, speech, and image sources are given. The SA method is guaranteed to perform in a globally optimal manner, and the SR technique gives empirical results equivalent to those of SA. Both techniques result in significantly better performance than that obtained with the generalized Lloyd Algorithm. >
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Globally Optimal Vector Quantizer Design by
1992Co-Authors: Kenneth Zeger, Jacques Vaisey, Allen GershoAbstract:This paper presents a unified formulation and study of vector quantizer design methods that couple stochastic re- laxation (SR) techniques with the generalized Lloyd Algorithm. Two new SR techniques are investigated and compared: simu- lated annealing (SA), and a reduced-complexity approach that modifies the traditional acceptance criterion for simulated an- nealing to an unconditional acceptance of perturbations. It is shown that four existing techniques all fit into a general meth- odology for vector quantizer design aimed at finding a globally optimal solution. Comparisons of each Algorithms' perfor- mance when quantizing Gauss-Markov processes, speech, and image sources are given. The SA method is guaranteed to per- form in a globally optimal manner, and the SR technique gives empirical results equivalent to those of SA. Both techniques re- sult in significantly better performance than that obtained with the generalized Lloyd Algorithm.
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Competitive learning and soft competition for vector quantizer design
IEEE Transactions on Signal Processing, 1992Co-Authors: E. Yair, Kenneth Zeger, Allen GershoAbstract:The authors provide a convergence analysis for the Kohonen learning Algorithm (KLA) with respect to vector quantizer (VQ) optimality criteria and introduce a stochastic relaxation technique which produces the global minimum but is computationally expensive. By incorporating the principles of the stochastic approach into the KLA, a deterministic VQ design Algorithm, the soft competition scheme (SCS), is introduced. Experimental results are presented where the SCS consistently provided better codebooks than the generalized Lloyd Algorithm (GLA), even when the same computation time was used for both Algorithms. The SCS may therefore prove to be a valuable alternative to the GLA for VQ design. >
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Corrections to 'Gradient Algorithms for designing predictive vector quantizers'
IEEE Transactions on Signal Processing, 1991Co-Authors: Kenneth ZegerAbstract:An error in a paper by Chang and Gray (see ibid., vol.34, no.4, p.679-90, 1986) is pointed out and corrected. The error invalidates their observation that the generalized Lloyd Algorithm is a gradient descent technique but the generalized Lloyd Algorithm is a member of the related class of coordinate descent techniques. Convergence rate analysis of gradient descent Algorithms for vector quantizer design is provided. >
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ICASSP - A parallel processing Algorithm for vector quantizer design based on subpartitioning
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics Speech and Signal Processing, 1991Co-Authors: Kenneth Zeger, Allen GershoAbstract:A technique for designing vector quantizers that is well suited for parallel processing environments is presented. The input space is iteratively partitioned into M disjoint connected regions composed of unions of partition regions. Each of M processors then independently commutes an optimal subquantizer for its restricted input space. The partitions can regularly be changed to further improve the overall quantizer performance. This technique can improve on the performance of the generalized Lloyd Algorithm by following the traditional design process with the subpartitioning iterations. >
Fujiki Morii - One of the best experts on this subject based on the ideXlab platform.
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a supervised Lloyd Algorithm and segmentation of handwritten japanese characters
European Signal Processing Conference, 1998Co-Authors: Fujiki MoriiAbstract:A generalization of a supervised Lloyd Algorithm to multilevel image thresholding is provided, whose Algorithm is an iterative and fast one based on a minimum weighted-squared distortion criterion. After deriving an important relation between weight coefficients in the criterion and convergent thresholds, we consider a procedure on a reasonable selection of the weight coefficients by a supervisor through segmentation experiments. Using these results, the segmentation of the ETL8 handwritten Japanese character data base is studied.
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EUSIPCO - A supervised Lloyd Algorithm and segmentation of handwritten Japanese characters
1998Co-Authors: Fujiki MoriiAbstract:A generalization of a supervised Lloyd Algorithm to multilevel image thresholding is provided, whose Algorithm is an iterative and fast one based on a minimum weighted-squared distortion criterion. After deriving an important relation between weight coefficients in the criterion and convergent thresholds, we consider a procedure on a reasonable selection of the weight coefficients by a supervisor through segmentation experiments. Using these results, the segmentation of the ETL8 handwritten Japanese character data base is studied.
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an image thresholding method using a minimum weighted squared distortion criterion
Pattern Recognition, 1995Co-Authors: Fujiki MoriiAbstract:We present a new thresholding method for image segmentation in which thresholds are selected on the basis of a minimum weighted squared-distortion criterion. An iterative Algorithm, which is named a supervised Lloyd Algorithm, to satisfy the criterion is derived. In order to achieve reliable segmentation, we discuss how the weight coefficients of the criterion must be tuned by a supervisor. Two supervised approaches based on a probabilistic histogram model and typical images in processing images are treated in detail.
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Generalization of Lloyd's Algorithm for image segmentation
Intelligent Robots and Computer Vision IX: Algorithms and Techniques, 1991Co-Authors: Fujiki MoriiAbstract:A generalized Lloyd Algorithm having a tuning parameter for image segmentation is investigated,whose Algorithm is derived from a minimum weighted squared distortion criterion to select a suitablethreshold from histogram information. We consider how to control the parameter of the Algorithmby supervised approaches to realize reliable segmentation. Two approaches based on a probabilistichistogram model and a typical image in processing images are treated in detail.
Jianzhong Zhang - One of the best experts on this subject based on the ideXlab platform.
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a novel and efficient vector quantization based cpri compression Algorithm
IEEE Transactions on Vehicular Technology, 2017Co-Authors: Hongbo Si, Md. Saifur Rahman, Boon Loong Ng, Jianzhong ZhangAbstract:The future wireless network, such as the Centralized Radio Access Network (C-RAN), will need to deliver data rate about 100–1000 times the current fourth-generation (4G) technology. For the C-RAN-based network architecture, there is a pressing need for tremendous enhancement of the effective data rate of the common public radio interface (CPRI). Compression of CPRI data is one of the potential enhancements. In this paper, we introduce a vector quantization based compression Algorithm for CPRI links, utilizing the Lloyd Algorithm. Methods to vectorize the I/Q samples and enhanced initialization of the Lloyd Algorithm for codebook training are investigated for improved performance. Multistage vector quantization and unequally protected multigroup quantization are considered to reduce codebook search complexity and codebook size. Simulation results show that our solution can achieve compression of four times for uplink and 4.5 times for downlink, within $2\%$ error vector magnitude (EVM) distortion. Remarkably, vector quantization codebook proves to be quite robust against data modulation mismatch, fading, signal-to-noise ratio (SNR), and Doppler spread.
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GLOBECOM - A Vector Quantization Based Compression Algorithm for CPRI Link
2015 IEEE Global Communications Conference (GLOBECOM), 2015Co-Authors: Si Hongbo, Saifur Rahman, Jianzhong ZhangAbstract:The future wireless networks, such as Centralized Radio Access Network (C-RAN), will need to deliver data rate about 100 times to 1000 times the current 4G technology. For C-RAN based network architecture, there is a pressing need for tremendous enhancement of the effective data rate of the Common Public Radio Interface (CPRI). Compression of CPRI data is one of the potential enhancements. We introduce a vector quantization based compression Algorithm for CPRI links, utilizing Lloyd Algorithm. Methods to vectorize the I/Q samples and enhanced initialization of Lloyd Algorithm for codebook training are investigated for improved performance. Multi-stage vector quantization is considered to reduce codebook search complexity. Simulation results show that our solution can achieve compression of 4 times for uplink and 4.5 times for downlink, within 2% Error Vector Magnitude (EVM) distortion. Remarkably, vector quantization codebook proves to be quite robust against data modulation mismatch, fading, signal-to-noise (SNR) and Doppler spread.
Victor B Lawrence - One of the best experts on this subject based on the ideXlab platform.
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bandwidth efficient bit and power loading for underwater acoustic ofdm communication system with limited feedback
Vehicular Technology Conference, 2011Co-Authors: Xiaopeng Huang, Victor B LawrenceAbstract:Adaptive bit and power loading is a constraint optimization problem with generally two cases of practical interest, where the objectives are the achievable data rate maximization (RM) and system margin maximization (MM) \cite{Ni-2008}. In this paper, we propose a different optimization model for underwater acoustic (UWA) channels, which is achieved by two Algorithms: one is the bandwidth-efficient bit loading Algorithm; the other is the Lloyd Algorithm based limited feedback procedure. It aims at minimizing the power consumption with constraints of the constant symbol data rate and desired bit-error-rate (BER). The optimization result is derived by the Lagrange multiplier method. The Lloyd Algorithm is employed to quantize the CSI at the receiver and construct the codebook, which is adopted to achieve the limited feedback process. After selecting an initial bit loading vector upon the current CSI, the receiver will broadcast its index to the transmitter, then the transmitter will compute the bandwidth-efficient bit loading Algorithm and allocate the corresponding power and bits to each subcarrier. Simulation results will reveal the benefits of adopting these two Algorithms from different aspects.
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VTC Spring - Bandwidth-Efficient Bit and Power Loading for Underwater Acoustic OFDM Communication System with Limited Feedback
2011 IEEE 73rd Vehicular Technology Conference (VTC Spring), 2011Co-Authors: Xiaopeng Huang, Victor B LawrenceAbstract:Adaptive bit and power loading is a constraint optimization problem with generally two cases of practical interest, where the objectives are the achievable data rate maximization (RM) and system margin maximization (MM) \cite{Ni-2008}. In this paper, we propose a different optimization model for underwater acoustic (UWA) channels, which is achieved by two Algorithms: one is the bandwidth-efficient bit loading Algorithm; the other is the Lloyd Algorithm based limited feedback procedure. It aims at minimizing the power consumption with constraints of the constant symbol data rate and desired bit-error-rate (BER). The optimization result is derived by the Lagrange multiplier method. The Lloyd Algorithm is employed to quantize the CSI at the receiver and construct the codebook, which is adopted to achieve the limited feedback process. After selecting an initial bit loading vector upon the current CSI, the receiver will broadcast its index to the transmitter, then the transmitter will compute the bandwidth-efficient bit loading Algorithm and allocate the corresponding power and bits to each subcarrier. Simulation results will reveal the benefits of adopting these two Algorithms from different aspects.