Abstract
One of the main goals of signal analysis has been the development of signal representations in terms of elementary waveforms or atoms. Dictionaries are collections of atoms with common parameterized features. We present a pursuit methodology to optimize redundant atomic representations from several dictionaries. The architecture exploits notions of modularity and coadaptation between atoms, in order to evolve an optimized signal representation. Modularity is modeled by dictionaries. Coadaptation is promoted by introducing self-adaptive, gene expression weights associated with the genetic representation of a signal in a proper dictionary space. The proposed model is tested on atomic pattern recognition problems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Stéphane Mallat. A Wavelet Tour of Signal Processing. Academic Press, San Diego, 1998.
S.S. Chen. Basis Pursuit. PhD thesis, Stanford University, November 1995.
G.M. Davis, S. Mallat, and M. Avelanedo. Greedy adaptive approximations. J. Constr. Approx., 13:57–98, 1997.
Thomas Bäck. Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford University Press, New York, 1996.
H.-G. Beyer. Towards a theory of evolution strategies: Self-adaptation. Evolutionary Computation, 3(3):311–347, 1996.
A.F. da Silva. Genetic algorithms for component analysis. In D. Whitley et. al., editor, Proceedings of the 2000 Genetic and Evolutionary Computation Conference, GECCO-2000, Las Vegas, Nevada, pages 243–250. Morgan Kaufmann Publishers, San Francisco, 2000.
A.F. da Silva. Evolutionary time-frequency analysis. In A. Zalzala et. al., editor, Proceedings of the 2000 Congress on Evolutionary Computation, CEC 2000, La Jolla, California, pages 1102–1109. IEEE Press, 2000.
H. Kargupta. The genetic code and the genome representation. In Annie S. Wu, editor, Proceedings of the 2000 Genetic and Evolutionary Computation Conference Workshop Program, pages 179–184, 2000.
M. Wall. GAlib: A C++ Library of Genetic Algorithm Components. Mechanical Engineering Department, Massachusetts Institute of Technology, August 1996.
K. Chellapilla. Combining mutation operators in evolutionary programming. IEEE Trans. on Evolutionary Computation, 2(3):91–96, September 1998.
A.F. da Silva. Evolutionary wavelet bases in signal spaces. In S. Cagnoni et al., editor, Real-World Applications of Evolutionary Computing, volume 1803 of Lecture Notes in Computer Science, pages 44–53. Springer-Verlag, 2000.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
da Ferreira Silva, A.R. (2001). A Pursuit Architecture for Signal Analysis. In: Boers, E.J.W. (eds) Applications of Evolutionary Computing. EvoWorkshops 2001. Lecture Notes in Computer Science, vol 2037. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45365-2_32
Download citation
DOI: https://doi.org/10.1007/3-540-45365-2_32
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41920-4
Online ISBN: 978-3-540-45365-9
eBook Packages: Springer Book Archive