Presentation 2003/5/22
A High-Performance Processor Dedicated to Codebook Design for Vector Quantization
Chiaki TAKAGI, Ryusuke EGAWA, Kentaro SANO, Tadao NAKAMURA,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Vector quantization(VQ) is an attractive technique for lossy data compression, which has been a key technology for data storage and/or transfer. So far, various algorithms have been proposed to design optimal codebooks presenting quantization with minimized errors. However, the amount of computation for codebook design is extremely huge for large data sets, restricting applications of optimal vector quantization. This paper provides massively parallel architecture for a VQ processor. This VQ processor performs modified Kohonen learning where delayed update of codebooks is introduced. Software simulation gave results denoting that the delayed update does not introduce serious increase of errors. The VQ Processor consists of code-vector cells on a 2D grid. The synopsys design compiler provided the critical path of 15.00 ns for the code-vector cell designed by using the ROHM 0.35 μm CMOS process technology.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) vector quantization / codebook design / functional memory / massively parallel processing
Paper # NC2003-6
Date of Issue

Conference Information
Committee NC
Conference Date 2003/5/22(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A High-Performance Processor Dedicated to Codebook Design for Vector Quantization
Sub Title (in English)
Keyword(1) vector quantization
Keyword(2) codebook design
Keyword(3) functional memory
Keyword(4) massively parallel processing
1st Author's Name Chiaki TAKAGI
1st Author's Affiliation Graduate School of Information Science, Tohoku University()
2nd Author's Name Ryusuke EGAWA
2nd Author's Affiliation Graduate School of Information Science, Tohoku University
3rd Author's Name Kentaro SANO
3rd Author's Affiliation Graduate School of Information Science, Tohoku University
4th Author's Name Tadao NAKAMURA
4th Author's Affiliation Graduate School of Information Science, Tohoku University
Date 2003/5/22
Paper # NC2003-6
Volume (vol) vol.103
Number (no) 92
Page pp.pp.-
#Pages 6
Date of Issue