Internet Information Retrieval, Parallel Sorting, and Rank-Order Filtering Based on Dynamical Neural Circuits of Maximal Value Signal Identification Among Discrete-Time Signals
The design of mathematical models and corresponding functional block-diagrams of discrete-time neural networks for Internet information retrieval, parallel sorting, and rankorder filtering is proposed. The networks are based on the discrete-time dynamical K-winnerstake-all (KWTA) neural circuits which can identify the K largest from N input signals, where 1£ < K N is a positive integer. Implementation prospects of the networks in an up-to date digital hardware are outlined.