DocumentCode :
2330595
Title :
Vector quantization complexity and quantum computing
Author :
Gastaldo, Paolo ; Ridella, Sandro ; Zunino, Rodolfo
Author_Institution :
Dept. Biophys. & Electron. Eng., Genoa Univ., Genova, Italy
Volume :
4
fYear :
2004
fDate :
25-29 July 2004
Firstpage :
3257
Abstract :
A dichotomy between ´analogue´ modeling and ´digital´ implementation is often encountered when designing vector quantizers. In the case of digital systems, the requirement of optimality can bring about NP-hard problems. The paper discusses the possibility of using advanced paradigms such as quantum computing for digital optimization processes in order to overcome the limitations of conventional machinery. The presented research provides analytical criteria determining the relative advantages of conventional over quantum-computing approaches.
Keywords :
computational complexity; optimisation; quantum computing; vector quantisation; NP-hard problem; digital optimization process; quantum computing; vector quantization complexity; Cost function; Design engineering; Digital systems; Machinery; NP-hard problem; Optimization methods; Polynomials; Prototypes; Quantum computing; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Conference_Location :
Budapest
ISSN :
1098-7576
Print_ISBN :
0-7803-8359-1
Type :
conf
DOI :
10.1109/IJCNN.2004.1381201
Filename :
1381201
Link To Document :
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