DocumentCode :
2707598
Title :
On global optimality of gradient descent algorithms for fixed-rate scalar multiple description quantizer design
Author :
Dumitrescu, Sorina ; Wu, Xiaolin
Author_Institution :
Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada
fYear :
2005
fDate :
29-31 March 2005
Firstpage :
388
Lastpage :
397
Abstract :
We prove that Trushkin´s (1982) sufficient conditions for the global optimality of a locally optimal fixed-rate scalar quantizer also ensure the global optimality of a locally optimal fixed-rate multiple description scalar quantizer of convex codecells, with respect to a fixed index assignment. This result also holds for the fixed-rate multiresolution scalar quantizer of convex codecells. As a consequence the well-known log-concave pdf condition can be extended to the multiple description and multiresolution case.
Keywords :
codes; gradient methods; optimisation; probability; vector quantisation; convex codecells; fixed index assignment; fixed-rate quantizer design; global optimality; gradient descent algorithms; log-concave pdf condition; multiresolution scalar quantizer; scalar multiple description quantizer; Algorithm design and analysis; Data compression; Probability density function; Probability distribution; Quantization; Random variables; Sufficient conditions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Compression Conference, 2005. Proceedings. DCC 2005
ISSN :
1068-0314
Print_ISBN :
0-7695-2309-9
Type :
conf
DOI :
10.1109/DCC.2005.60
Filename :
1402200
Link To Document :
بازگشت