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Vector quantization based on genetic simulated annealing

Hsiang-Cheh Huang, Jeng-Shyang Pan, Zhe-Ming Lu, Sheng-He Sun, Hsueh-Ming Hang
2001 Signal Processing  
Genetic algorithm (GA) has been successfully applied to codebook design for vector quantization (VQ).  ...  In addition, simulated annealing (SA) algorithm is also used in GVQ to get more promising results and the corresponding method is referred to as GSAVQ.  ...  ect on the Nomenclature VQ vector quantization GA genetic algorithm GVQ genetic vector quantization GSAVQ genetic simulated annealing vector quantization SA simulated annealing LBG conventional codebook  ... 
doi:10.1016/s0165-1684(01)00048-2 fatcat:c7jfr7ijpjhv3ppjbt5pdmy2lq

Parallelization of the LBG Vector Quantization Algorithm for Shared Memory Systems [article]

Rajashekar Annaji, Shrisha Rao
2009 arXiv   pre-print
This parallel algorithm addresses the problem of designing an optimum codebook using the traditional LBG type of vector quantization algorithm for shared memory systems and for the efficient usage of parallel  ...  This paper proposes a parallel approach for the Vector Quantization (VQ) problem in image processing.  ...  Some of the algorithms that have been used for sequential VQ codebook generation are LBG, pair wise nearest neighbor(PNN), simulated annealing, and fuzzy c-means clustering [10] analysis.  ... 
arXiv:0910.4711v1 fatcat:rov4che7sbelbkpeozms2ocxuq

Combining modulation diversity and index assignment to improve image VQ for a rayleigh fading channel

Waslon Terllizzie Araújo Lopes, Francisco Madeiro, Benedito Guimarães Aguiar Neto, Marcelo Sampaio de Alencar
2004 Learning and Nonlinear Models  
Vector quantization (VQ) has been widely used in many image coding systems.  ...  In the present paper, modulation diversity (MD) is combined with index assignment (IA) by simulated annealing for improving the transmission of vector quantized images over a Rayleigh fading channel: MD  ...  Vector quantization is briefly described in Section 2, with a focus on VQ for noisy channels. Section 3 describes the application of simulated annealing for index assignment.  ... 
doi:10.21528/lnlm-vol2-no1-art3 fatcat:sukmyki3rjhavouug6tclfcdmi

Robust vector quantization for wireless channels

Wen-Whei Chang, Tan-Hsu Tan, De-Yu Wang
2001 IEEE Journal on Selected Areas in Communications  
This study focuses on two issues: parametric modeling of the channel and index assignment of codevectors, to design a vector quantizer that achieves high robustness against channel errors.  ...  We first formulate the design of a robust zero-redundancy vector quantizer as a combinatorial optimization problem leading to a genetic search for a minimum-distortion index assignment.  ...  These results are presented for a vector quantizer with a codebook size and vector dimension of .  ... 
doi:10.1109/49.932703 fatcat:k32mkhoeyzezxnno4x6cj4gf7a

Predictive vector quantizer design using deterministic annealing

H. Khalil, K. Rose
2003 IEEE Transactions on Signal Processing  
Index Terms-Closed-loop design, deterministic annealing, open-loop design, predictive vector quantizer design.  ...  Its probabilistic framework replaces hard quantization with a differentiable expected cost function that can be jointly optimized for the predictor and quantizer parameters, and its annealing schedule  ...  is quantized to codebook entry .  ... 
doi:10.1109/tsp.2002.806582 fatcat:wicnvnffqnhxvjesxmulwtbv4y

NSVQ: Noise Substitution in Vector Quantization for Machine Learning

Mohammad Hassan Vali, Tom Backstrom
2022 IEEE Access  
This study proposes a vector quantization technique called NSVQ, which approximates the vector quantization behavior by substituting a multiplicative noise so that it can be used for machine learning problems  ...  Specifically, the vector quantization error is replaced by product of the original error and a normalized noise vector, the samples of which are drawn from a zero-mean, unit-variance normal distribution  ...  For that purpose, let us define a generic loss function which takes the simulated quantization as input l(x ).  ... 
doi:10.1109/access.2022.3147670 fatcat:h5s4dgl45nf2bfyqhleipy45iq

Design of Sample Adaptive Product Quantizers for Noisy Channels

Z. Raza, F. Alajaji, T. Linder
2005 IEEE Transactions on Communications  
In this letter, we generalize the design of SAPQ for the case of memoryless noisy channels by optimizing the quantizer with respect to both source and channel statistics.  ...  Index Terms-Channel-optimized quantization, encoding/ storage complexity, joint source-channel coding, structurally constrained vector quantization.  ...  Each of the codebooks is that of a product quantizer (PQ) (e.g., see [6] and [7] ), and the choice of the particular codebook used for encoding depends on the source vector.  ... 
doi:10.1109/tcomm.2005.844938 fatcat:4y3xpilq5zchvksho5mplbppsa

Vector quantization with complexity costs

J. Buhmann, H. Kuhnel
1993 IEEE Transactions on Information Theory  
Vector quantization is a data compression method where a set of data points is encoded by a reduced set of reference vectors, the codebook.  ...  We discuss a vector quantization strategy which jointly optimizes distortion errors and the codebook complexity, thereby, determining the size of the codebook.  ...  Tavan for helpful discussions and two anonymous reviewers for useful suggestions to improve the manuscript. JB acknowledges  ... 
doi:10.1109/18.243432 fatcat:sb4nybqjz5ehxd2pewlmb5mxiq

A competitive continuous Hopfield neural network for vector quantization in image compression

J.-S. Lin, S.-H. Liu
1999 Engineering applications of artificial intelligence  
In this paper, a parallel approach using the competitive continuous Hop®eld neural network (CCHNN) is proposed for the vector quantization in image compression.  ...  In CCHNN, the codebook design is conceptually considered as a clustering problem.  ...  Another vector-quantized design algorithm, which incorporates simulated annealing and the Lloyd iteration, was proposed by Zeger et al. (1992) .  ... 
doi:10.1016/s0952-1976(98)00056-6 fatcat:toelmjqnefhf7k4bjpdf6atvdi

Reduced-Complexity Deterministic Annealing for Vector Quantizer Design

Kemal Demirciler, Antonio Ortega
2005 EURASIP Journal on Advances in Signal Processing  
This paper presents a reduced-complexity deterministic annealing (DA) approach for vector quantizer (VQ) design by using soft information processing with simplified assignment measures.  ...  We use the derived result to obtain optimal annealing schedules for the simple soft measures that approximate the annealing schedule for the optimal Gibbs distribution.  ...  An important SR technique is simulated annealing (SA) [9] , where in each iteration a new codebook is generated in the neighborhood of the old one, and the new codebook is accepted or rejected according  ... 
doi:10.1155/asp.2005.1807 fatcat:efsfebgp4vd7haxrseawmsbnpi

Competitive learning algorithms for robust vector quantization

T. Hofmann, J.M. Buhmann
1998 IEEE Transactions on Signal Processing  
We show an exemplary application of the novel robust vector quantization algorithm to image compression for a teleconferencing system.  ...  In this paper, we propose a unifying approach to data compression by robust vector quantization, which explicitly deals with channel noise, bandwidth limitations, and random elimination of prototypes.  ...  The General Robust Vector Quantization ModelThe general robust vector quantization model which unies the maximum entropy principle with channel noise and random prototype eliminations is governed by the  ... 
doi:10.1109/78.678486 fatcat:pyxwrynom5dohcqvcul5hqyroq

LSQ++: Lower Running Time and Higher Recall in Multi-codebook Quantization [chapter]

Julieta Martinez, Shobhit Zakhmi, Holger H. Hoos, James J. Little
2018 Lecture Notes in Computer Science  
Multi-codebook quantization (MCQ) is the task of expressing a set of vectors as accurately as possible in terms of discrete entries in multiple bases.  ...  However, recent studies and methods in this area are hard to compare against each other, because they use different datasets, different protocols, and, perhaps most importantly, different computational  ...  We thank NVIDIA for the donation of GPUs used in this project. Shobhit was supported by a Mitacs Globalink research internship while at UBC.  ... 
doi:10.1007/978-3-030-01270-0_30 fatcat:k6mf4nwwfbe2tmov26364mtln4

Multi-resolution Mean-Shift Algorithm for Vector Quantization

P. L. M. Bouttefroy, A. Bouzerdoum, A. Beghdadi, S. L. Phung
2010 2010 Data Compression Conference  
We propose an approach based on mean-shift, invoking the multi-resolution framework to generate codebook vectors.  ...  The generation of stratified codebooks, providing a subset of vectors at different scale levels, has become necessary with the emergence of embedded coder/decoder for scalable image and video formats.  ...  The simulated annealing technique traditionally used to identify the modes of the distribution for different resolutions can be performed by exploration of the multi-scale DWT pyramid, avoiding the costly  ... 
doi:10.1109/dcc.2010.55 dblp:conf/dcc/BouttefroyBBP10 fatcat:joy6cr44azfq3c5xfqn3btkgq4

Model-free functional MRI analysis based on unsupervised clustering

Axel Wismüller, Anke Meyer-Bäse, Oliver Lange, Dorothee Auer, Maximilian F. Reiser, DeWitt Sumners
2004 Journal of Biomedical Informatics  
A comparison of this new method with KohonenÕs self-organizing map and with a fuzzy clustering scheme based on deterministic annealing is done in a systematic fMRI study showing comparative quantitative  ...  clustering technique outperform KohonenÕs map in terms of identifying signal components with high correlation to the fMRI stimulus, (2) the "neural gas" outperforms the two other methods with respect to the quantization  ...  (A) Cluster assignment map, (B) codebook vector.  ... 
doi:10.1016/j.jbi.2003.12.002 pmid:15016382 fatcat:ifzdabczuvgojc4oxjg3edcjka

A new initialization technique for generalized Lloyd iteration

I. Katsavounidis, C.-C. Jay Kuo, Zhen Zhang
1994 IEEE Signal Processing Letters  
The generalized Lloyd algorithm plays an important role in the design of vector quantizers (VQ) and in feature clustering fdr pattern recognition.  ...  In this research, we propose an efficient method to obtain a good initial codebook that can accelerate the convergence of the generalized Lloyd algorithm and achieve a better local minimum as well.  ...  Zeger et al. [5] proposed to use stochastic relaxation, such as the simulated annealing method, to achieve a better result than GLA.  ... 
doi:10.1109/97.329844 fatcat:xbflbmbatbhsxj5cw6lykdvbf4
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