Selecting the best wavelet packet pier inspired by biological methods

  • Alireza Rezaee university of tehran
Keywords: wavelet packets, best basis, the best level of analysis, genetic algorithms, variable-length Chromosome, shannon entropy

Abstract

In this project, a new method for selecting the best wavelet packet pier is presented. The method of complex organisms from simple gradual chromosomes early to more complex organisms have been inspired by the current. In this algorithm, first, the best pier to the lowest level of analysis based on the shannon entropy measure using Genetic Algorithm (GA) is selected, then the pier to create optimal early population to a higher level is used and the work until the last level of analysis is repeated. The results show that this way, with a gradual increase during chromosomes best wavelet packet pier with higher convergence rate, higher accuracy and less computation than previous methods is selected. In addition, previous methods based on GA, the best possible level of analysis did not exist, but this method, access is provided.

References

[1] T.Schell, A. Uhi, “Optimization and Assessment of Wavelet Packet Decompositions with Evolutionary Computation”, EURASIP Journal on Applied Signal Processing, 806-813, August 2003.
[2] Peng Xu, Chan, A.K., “Optimal wavelet sub-band Selection using Genetic Algorithm”, Geoscience and Remote Sensing Symposium, 2002, IGARSS ’02, 2002 IEEE International, vol.3, pp.1441-1443, June 2002 .
[3] Il Yong KIM, O. De Weck, “Variable Chromosome Length Genetic Algorithm for Structural Topology Design Optimization”, 45th, Structural Dynamics & Materials Conference, April 2004.

[4] R. R. Coifman, M. V. Wickerhauser, “Entropy-Based Algorithms for Best Basis Selection”, IEEE Transactions on information theory, VOL. 38, NO. 2, March 1992.

[5] M. V. Wickerhauser, “Adapted Wavelet Analysis from Theory to Software”, A. K. Peters,Wellesley, Mass, USA, 1994.

[6] C. Taswell, “Near-best basis selection algorithms with nonadditive information cost functions”, in Proc. IEEE International Symposium on Time-Frequency and Time-Scale Analysis (TFTS ’94), M. Amin, Ed., pp. 13–16, IEEE Press, Philadelphia,
Pa, USA, October 1994.

[7] S.G. Mallat, “A theory for multiresolution signal decomposition: The wavelet representation”, IEEE Trans. Pattern Anal. Machine Intell., vol. 11, pp. 674-693, July 1989.

[8] C.Sidney Burrus, Ramesh A. Gopinath, Haitao Gue, “Introduction to Wavelets and Wavelet Transforms”, New Jersy: Prentice Hall, 1st edition, 1998.
Published
2017-03-20
How to Cite
Rezaee, A. (2017). Selecting the best wavelet packet pier inspired by biological methods. Majlesi Journal of Telecommunication Devices, 6(1). Retrieved from http://journals.iaumajlesi.ac.ir/td/index/index.php/td/article/view/393
Section
Articles