Learning a multi-dimensional companding function for lossy source coding

DOI10.1016/J.NEUNET.2009.06.001zbMath1335.94021DBLPjournals/nn/MaedaI09OpenAlexW2090667368WikidataQ51616521 ScholiaQ51616521MaRDI QIDQ280417

Shin Ishii, Shin-ichi Maeda

Publication date: 10 May 2016

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2009.06.001

zbMATH Keywords

vector quantizationbit allocationcompanding functionlossy source coding

Mathematics Subject Classification ID

Source coding (94A29)

Uses Software

• darch
• MNIST

Cites Work

• Reducing the Dimensionality of Data with Neural Networks
• A lower bound on the average error of vector quantizers (Corresp.)
• Suboptimality of the Karhunen–LoÈve Transform for Transform Coding
• Companding and random quantization in several dimensions
• Bit allocation and encoding for vector sources
• Asymptotically optimal block quantization
• Transform coding with backward adaptive updates
• Least squares quantization in PCM
• Bennett's integral for vector quantizers

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