DocumentCode
1072415
Title
Efficient quantization for overcomplete expansions in RN
Author
Beferull-Lozano, Baltasar ; Ortega, Antonio
Author_Institution
Dept. of Electr. Eng.-Syst., Univ. of Southern California, Los Angeles, CA, USA
Volume
49
Issue
1
fYear
2003
fDate
1/1/2003 12:00:00 AM
Firstpage
129
Lastpage
150
Abstract
We study construction of structured regular quantizers for overcomplete expansions in RN. Our goal is to design structured quantizers which allow simple reconstruction algorithms with low complexity and which have good performance in terms of accuracy. Most related work to date in quantized redundant expansions has assumed that the same uniform scalar quantizer was used on all the expansion coefficients. Several approaches have been proposed to improve the reconstruction accuracy, with some of these methods having significant complexity. Instead, we consider the joint design of the overcomplete expansion and the scalar quantizers (allowing different step sizes) in such a way as to produce an equivalent vector quantizer (EVQ) with periodic structure. The construction of a periodic quantizer is based on lattices in RN and the concept of geometrically scaled- similar sublattices. The periodicity makes it possible to achieve good accuracy using simple reconstruction algorithms (e.g., linear reconstruction or a small lookup table).
Keywords
quantisation (signal); signal reconstruction; signal sampling; efficient quantization; equivalent vector quantizer; expansion coefficients; geometrically scaled-similar sublattices; linear reconstruction; lookup table; low complexity algorithms; overcomplete expansions; oversampled A/D; periodic quantizer; periodic structure; quantized redundant expansions; reconstruction accuracy; reconstruction algorithms; sinusoid signals; step sizes; structured regular quantizers; uniform scalar quantizer; Acoustical engineering; Additive white noise; Algorithm design and analysis; Lattices; Periodic structures; Quantization; Reconstruction algorithms; Signal representations; Table lookup; Vectors;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.2002.806117
Filename
1159767
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