An application of the principle of maximum information preservation to linear systems
Advances in neural information processing systems 1
Spatio-temporal adaptation in the unsupervised development of networked visual neurons
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
This note presents a local learning rule that enables a network to maximize the mutual information between input and output vectors. The network's output units may be nonlinear, and the distribution of input vectors is arbitrary. The local algorithm also serves to compute the inverse C-1 of an arbitrary square connection weight matrix.