Title :
Boolean neural network realization for mirror symmetry cases
Author :
Du, Xinyu ; Singh, Harpreet ; Ying, Hao
Author_Institution :
Dept. of Electr. & Comput. Eng., Wayne State Univ., Detroit, MI, USA
Abstract :
Boolean neural networks are a class of neural networks in which input and output are Boolean. A general algorithm for mirror symmetry cases in Boolean neural network is presented. The new algorithm provides a systematic transform method to reduce the number of compact zones (hidden units) instead of trial method for the mirror symmetry cases with IMS method previously available in literature. The properties of the algorithm are given and demonstrated by some examples. A simulation of the proposed algorithm has also been made.
Keywords :
Boolean functions; neural nets; transforms; Boolean neural network; implied minterm structure; mirror symmetry; transform method; Birth disorders; Computer networks; Input variables; Mirrors; Neural networks; Neurons;
Conference_Titel :
Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American
Print_ISBN :
0-7803-9187-X
DOI :
10.1109/NAFIPS.2005.1548636