Work

A Recursive Quantizer Design Algorithm for Binary-Input Discrete Memoryless Channels

Year: 2021

Type: article

Abstract: The optimal quantization of output binary-input discrete memoryless channels is considered, whereby the optimal quantizer preserves at least a constant$\alpha $-fraction of the original mutual information, with the smallest output cardinality. Two recursive methods with top-down and bottom-up approaches are developed; these methods lead to a new necessary condition for the recursive quantizer design. An efficient algorithm with linear complexity, based on dynamic programming and the new necessary optimality condition, is proposed.

Source: IEEE Transactions on Communications

DOI: 10.1109/tcomm.2021.3076174

Authors: Mehdi Dabirnia, Alfonso Martinez, Albert Guillen i Fabregas

Institutions: Universitat Pompeu Fabra, Institució Catalana de Recerca i Estudis Avançats, University of Cambridge

Language: English

Topic: Advanced Data Compression Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Ministerio de Economía y Competitividad, European Research Council, H2020 European Research Council

Awards: Information Theory with Uncertain Laws, G4963644402, G5584361196, G5948820415