A Metaheuristic Approach to Two Dimensional Recursive Digital Filter Design View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Abhronil Sengupta , Tathagata Chakraborti , Amit Konar

ABSTRACT

The two dimensional IIR digital filter design problem has received increased attention over the past few years. Recently, several metaheuristic algorithms have been employed in this domain and have produced promising results. Invasive Weed Optimization is one of the latest population-based metaheuristic algorithms that mimics the colonizing action of weeds. In this chapter, an improvement to the classical weed optimization algorithm has been proposed by introducing a constriction factor in the seed dispersal phase. Temporal Difference Q-Learning has been employed to adapt this parameter for different population members through the successive generations. Such hybridization falls under a special class of adaptive Memetic Algorithms. The proposed memetic realization, called Intelligent Invasive Weed Optimization (IIWO), has been applied to the two-dimensional recursive digital filter design problem and it has outperformed several competitive algorithms that have been applied in this research field in the past. More... »

PAGES

167-182

Book

TITLE

Advances in Heuristic Signal Processing and Applications

ISBN

978-3-642-37879-9
978-3-642-37880-5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-37880-5_8

DOI

http://dx.doi.org/10.1007/978-3-642-37880-5_8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025810361


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