The number of metastable states of a simple perceptron with gradient descent learning algorithm
Elka Korutcheva · Journal of Physics A Mathematical and General · 1993
The number of metastable states of a simple perceptron with gradient descent learning algorithm has been calculated as a function of the storage capacity alpha and the gain parameter beta . For alpha not=0 and beta >0 exponential large number of local minima, similar to the spin glasses and analogue attractor networks, has been found.