Recursive procedure based on virtual state method for estimating connection value of nonlinear circuit associative network

The authors describe a novel associative network model of neural networks, and a novel algorithm for estimating the singular connecting matrix using the virtual state method in network learning. By this method the nonsingularized coefficient matrix can be estimated recursively by the escalator method. Therefore, learning the (k+1)th pattern can be done just by modifying the inverse matrix of the kth pattern slightly.<>