Title
Learning algorithms of bidirectional associative memory based on max-min criterion
Document Type
Article
Publication Date
8-1-1996
Abstract
A max-min criterion for design of bidirectional associative memory, which requires the smallest domain of attraction to be maximized, is proposed in this paper. A quick learning algorithm is first given, by which the designed connection weights are 1, 0 or-1. Further, a constrained perception optimization algorithm is presented, which takes the weights obtained by quick algorithm as initial iteration value. Computer experimental results confirm the advantages of the proposed algorithms.
Publication Source (Journal or Book title)
Tien Tzu Hsueh Pao/Acta Electronica Sinica
First Page
28
Last Page
32, 14
Recommended Citation
Liang, X., & Wu, L. (1996). Learning algorithms of bidirectional associative memory based on max-min criterion. Tien Tzu Hsueh Pao/Acta Electronica Sinica, 24 (8), 28-32, 14. Retrieved from https://repository.lsu.edu/eecs_pubs/876