Modified Memory Convergence with Fuzzy PSO

—Associative neural memories are models of biological phenomena that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. In this paper, we introduce fuzzy swarm particle optimization technique for convergence of associative neural memories based on fuzzy set theory. An FPSO consists of clustering of swarm’s particle by applying fuzzy c-mean algorithm to attain the neighborhood best. We present a singular value decomposition method for the selection of efficient rule from a given rule base required to attain the global best. Finally, we illustrate the proposed method by virtue of some examples.

• Type: Conference
• Year: 2007
• Where: WCE
• Authors: Subhash Chandra Pandey, P. K. Mishra
• Keywords: Fuzzy Swarm Particle, Neural Memories, WCE 2007, WCE 2008, —Associative Neural Memories