Novel vector quantiser design using reinforced learning as a pre-process
- Author
- WENHUAN XU1 ; NANDI, Asoke K1 ; JIHONG ZHANG2 ; EVANS, Kenneth G1
[1] Department of Electrical Engineering and Electronics, Signal Processing and Communications Group, University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, United Kingdom
[2] Information Engineering Faculty, Shenzhen University, Shenzhen 518060, China - Source
Signal processing. 2005, Vol 85, Num 7, pp 1315-1333, 19 p ; ref : 17 ref
- CODEN
- SPRODR
- ISSN
- 0165-1684
- Scientific domain
- Telecommunications
- Publisher
- Elsevier Science, Amsterdam
- Publication country
- Netherlands
- Document type
- Article
- Language
- English
- Author keyword
- FKM FRLVQ FVQ GLA LVQ Reinforced learning Vector quantisation
- Keyword (fr)
- Algorithme k moyenne Apprentissage renforcé Evaluation performance Logique floue Quantification vectorielle
- Keyword (en)
- K means algorithm Reinforcement learning Performance evaluation Fuzzy logic Vector quantization
- Keyword (es)
- Algoritmo k media Aprendizaje reforzado Evaluación prestación Lógica difusa Cuantificación vectorial
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D04 Telecommunications and information theory / 001D04A Information, signal and communications theory / 001D04A04 Signal and communications theory / 001D04A04C Sampling, quantization
- Discipline
- Telecommunications and information theory
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 16836712
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1016/j.sigpro.2004.12.012 
https://dx.doi.org/10.1016/j.sigpro.2004.12.012
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