Results 1 to 10 of about 178,862 (163)
Quantum Computing Approaches for Vector Quantization—Current Perspectives and Developments [PDF]
Entropy, 2023 In the field of machine learning, vector quantization is a category of low-complexity approaches that are nonetheless powerful for data representation and clustering or classification tasks. Vector quantization is based on the idea of representing a data
Alexander Engelsberger, Thomas Villmann
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Network Vector Quantization [PDF]
IEEE Transactions on Information Theory, 2004 We present an algorithm for designing locally optimal vector quantizers for general networks. We discuss the algorithm's implementation and compare the performance of the resulting "network vector quantizers" to traditional vector quantizers (VQs) and to rate-distortion (R-D) bounds where available.
Fleming, Michael +2 more
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Spherical-Cap Approximation of Vector Quantization for Quantization-Based Combining in MIMO Broadcast Channels with Limited Feedback [PDF]
Sensors, 2022 The spherical-cap approximation of vector quantization (SCVQ) is an analytical model used for the mathematical analysis of multiple-input multiple-output (MIMO) systems with limited feedback.
Moonsik Min, Tae-Kyoung Kim
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Greedy vector quantization [PDF]
Journal of Approximation Theory, 2015 31 pages, 4 figures, few typos corrected (now an extended version of an eponym paper to appear in Journal of Approximation)
Luschgy, Harald, Pagès, Gilles
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Multiresolution Vector Quantization [PDF]
IEEE Transactions on Information Theory, 2004 Multiresolution source codes are data compression algorithms yielding embedded source descriptions. The decoder of a multiresolution code can build a source reproduction by decoding the embedded bit stream in part or in whole. All decoding procedures start at the beginning of the binary source description and decode some fraction of that string ...
Effros, Michelle, Dugatkin, Diego
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Semilogarithmic Nonuniform Vector Quantization of Two-Dimensional Laplacean Source for Small Variance Dynamics [PDF]
Radioengineering, 2012 In this paper high dynamic range nonuniform two-dimensional vector quantization model for Laplacean source was provided. Semilogarithmic A-law compression characteristic was used as radial scalar compression characteristic of two-dimensional vector ...
Z. Peric, M. Savic, S. Panic
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Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design [PDF]
Sensors, 2016 The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used.
Edson Mata +4 more
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MECO: Mixture-of-Expert Codebooks for Multiple Dense Prediction Tasks [PDF]
SensorsAutonomous systems operating in embedded environments require robust scene understanding under computational constraints. Multi-task learning offers a compact alternative to deploying multiple task-specific models by jointly solving dense prediction ...
Gyutae Hwang, Sang Jun Lee
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Research on Quantization Parameter Decision Scheme for High Efficiency Video Coding
Applied Sciences, 2023 High-Efficiency Video Coding (HEVC) is one of the most widely studied coding standards. It still uses the block-based hybrid coding framework of Advanced Video Coding (AVC), and compared to AVC, it can double the compression ratio while maintaining the ...
Xuesong Jin, Yansong Chai
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NSVQ: Noise Substitution in Vector Quantization for Machine Learning
IEEE Access, 2022 Machine learning algorithms have been shown to be highly effective in solving optimization problems in a wide range of applications. Such algorithms typically use gradient descent with backpropagation and the chain rule.
Mohammad Hassan Vali, Tom Backstrom
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