DocumentCode :
1152027
Title :
Asymptotic entropy-constrained performance of tessellating and universal randomized lattice quantization
Author :
Linder, Tamas T. ; Zeger, Kenneth K.
Author_Institution :
Tech. Univ. Budapest, Hungary
Volume :
40
Issue :
2
fYear :
1994
fDate :
3/1/1994 12:00:00 AM
Firstpage :
575
Lastpage :
579
Abstract :
Two results are given. First, using a result of Csiszar (1973) the asymptotic (i.e., high-resolution/low distortion) performance for entropy-constrained tessellating vector quantization, heuristically derived by Gersho (1979), is proven for all sources with finite differential entropy. This implies, using Gersho´s conjecture and Zador´s formula, that tessellating vector quantizers are asymptotically optimal for this broad class of sources, and generalizes a rigorous result of Gish and Pierce (1968) from the scalar to the vector case. Second, the asymptotic performance is established for Zamir and Feder´s (1992) randomized lattice quantization. With the only assumption that the source has finite differential entropy, it is proven that the low-distortion performance of the Zamir-Feder universal vector quantizer is asympotically the same as that of the deterministic lattice quantizer
Keywords :
analogue-digital conversion; entropy; vector quantisation; Gersho´s conjecture; Zador´s formula; asymptotic entropy-constrained performance; entropy-constrained tessellating vector quantization; finite differential entropy; low-distortion; universal randomized lattice quantization; Automatic repeat request; Convolutional codes; Entropy; Error correction; Feedback; Information theory; Lattices; Maximum likelihood decoding; Quantization; Vector quantization; Viterbi algorithm;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/18.312189
Filename :
312189
Link To Document :
بازگشت