Improving the Hamming binary associative memory
暂无分享,去创建一个
The Hamming network is a binary associative memory which exhibits the maximum theoretically obtainable performance in terms of capacity and associativity. The structure is not ideal and two modifications which reduce the number of connections in the correlation matrix and in the selection layers are suggested. These modifications offer a significant reduction in the number of calculations required. >
[1] J J Hopfield,et al. Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.
[2] John Taylor,et al. Comparing performance of Hebbian- and delta-trained Hopfield networks , 1990 .
[3] Philip D. Wasserman,et al. Neural computing - theory and practice , 1989 .
[4] Richard P. Lippmann,et al. An introduction to computing with neural nets , 1987 .