Vector quantization based on steady-state memetic algorithm

被引：0

作者：

Ou C.-M. ^{[1
]}

机构：

[1] Department of Electronics Engineering, Ching-Yun University, Chungli

来源：

Journal of Marine Science and Technology | 2010年 / 18卷 / 04期

关键词：

Memetic algorithm; Steady-state genetic algorithm; Vector quantizer;

D O I：

10.51400/2709-6998.1912

中图分类号：

学科分类号：

摘要：

A novel memetic algorithm (MA) for the design of vector quantizers (VQs) is presented in this paper. The algorithm uses steady-state genetic algorithm (GA) for the global search and K-means algorithm for the local improvement. As compared with the usual MA using the generational GA for global search, the proposed MA dramatically reduces the computational time for VQ training. In addition, it attains a near global optimal solution, and its performance is insensitive to the selection of initial codewords. Numerical results show that it can save more than 70% of computation time while maintaining a comparable performance as previous MA.

引用

页码：553 / 557

页数：4

共 12 条

[1]

Areibi S., Moussa M., Abdullah H., A comparison of genetic/ memetic algorithms and heuristic searching, Proceedings of the 2001 International Conference on Artificial Intelligence, pp. 660-666, (2001)

[2]

Coe S., Areibi S., Moussa M., A hardware Memetic accelerator for VLSI circuit partitioning, Computers and Electrical Engineering, 33, 4, pp. 233-248, (2007)

[3]

Eiben A.E., Smith J.E., Introduction to Evolutionary Computing, (2003)

[4]

Gersho A., Gray R.M., Vector Quantization and Signal Compression, (1992)

[5]

Goldberg D.E., Deb K., A comparative analysis of selection schemes used in genetic algorithms, Fundations of Genetic Algorithms, pp. 69-93, (1991)

[6]

Kanungo T., Mount D.M., Netanyahu N.S., Piatko C.D., Silverman R., Wu A.Y., An efficient k-means clustering algorithms: Analysis and implementation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 7, pp. 881-892, (2002)

[7]

Lin T.K., Li H.Y., Hwang W.J., Ou C.M., Weng S.K., Genetic vector quantizer design on reconfigurable hardware, Lecture Notes in Computer Science, 5361, pp. 473-482, (2008)

[8]

Merz P., Freisleben B., Genetic algorithms for binary quadratic programming, Proceedings of the 1999 Genetic and Evolutionary Computation Conference, pp. 417-424, (1999)

[9]

Radcliffe N.J., Surry P.D., Formal memetic algorithms, Lecture Notes in Computer Science, 865, pp. 1-16, (1994)

[10]

Rasheed K., Davisson B.D., Effect of global parallelism on the behavior of a steady state genetic algorithm for design optimization, Proceedings of the Congress on Evolutionary Computation, 1, (1999)

← 1 2 →