The capacity of the semi-orthogonally associative memories model

This paper discusses the capacity of the SAM model and demonstrates that, in this model, there exists a paralysis index such that the recalling outputs converge to the desired pattern on initial inputs when the initial similar probability is larger than this index, or is not true. For any given neurons' number N, this index is a function of the characteristic parameter. The authors show how to determine the optimum characteristic parameter n of this model. The memory capacity of this model is N/2 ln ln N, and the capacity for storing information at each synaptic connection is larger than 1/2/spl pi/ bits.

[1]  BART KOSKO,et al.  Bidirectional associative memories , 1988, IEEE Trans. Syst. Man Cybern..

[2]  Shun-ichi Amari,et al.  Statistical neurodynamics of associative memory , 1988, Neural Networks.

[3]  James A. Anderson,et al.  A simple neural network generating an interactive memory , 1972 .

[4]  Yasumitsu Miyazaki,et al.  Connected Associative Memory Neural Network with Dynamical Threshold Function , 1992 .

[5]  Santosh S. Venkatesh,et al.  The capacity of the Hopfield associative memory , 1987, IEEE Trans. Inf. Theory.

[6]  Teuvo Kohonen,et al.  Correlation Matrix Memories , 1972, IEEE Transactions on Computers.

[7]  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.

[8]  Eric Goles Ch.,et al.  Decreasing energy functions as a tool for studying threshold networks , 1985, Discret. Appl. Math..