Abstract/Details

TRELLIS DATA COMPRESSION

STEWART, LAWRENCE COLM. 
 Stanford University ProQuest Dissertations Publishing,  1981. 8124158.

Abstract (summary)

Tree and trellis data compression systems have traditionally been designed by using a tree or trellis search algorithm to improve the performance of traditional coding systems such as adaptive delta modulation or predictive quantization. Recent work in the area of vector quantization has suggested the possibility of designing new tree and trellis codes which are well matched to particular sources. The main design procedure iterates on a long training sequence to improve the performance of an initial trellis decoder. An additional procedure, given a trellis decoder, can produce a decoder of longer constraint length which performs at least as well. Combined, these algorithms provide a complete design procedure for trellis encoding data compression systems.

For random sources, many existing data compression systems can be readily improved and performance close to the rate-distortion bound can be obtained. In the applications area of speech compression, tree and trellis codes designed with these algorithms permit the construction of low rate speech waveform coders, low rate residual excited linear predictive coders (RELP), and a new kind of hybrid tree coder which provides good quality speech at rates below 7000 bits per second.

Indexing (details)


Subject
Electrical engineering
Classification
0544: Electrical engineering
Identifier / keyword
Applied sciences
Title
TRELLIS DATA COMPRESSION
Author
STEWART, LAWRENCE COLM
Number of pages
137
Degree date
1981
School code
0212
Source
DAI-B 42/05, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9798660520624
University/institution
Stanford University
University location
United States -- California
Degree
Ph.D.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
8124158
ProQuest document ID
303177936
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
https://www.proquest.com/docview/303177936