Probabilistic Learning System (Sequential Pattern Recognition) U.S. Patent 4,599,693
A probabilistic learning system of the type that receives sequential input data and outputs sequences of recognized patterns. The system includes an array of interconnected probabilistic learning elements of the type that receive sequences of objects and outputs sequences of recognized states, the array of learning elements being interconnected to have a number of input learning elements and a number of output learning elements. The input data is partitioned between the input learning elements of the array so that the partitioned input data forms objects provided to the learning elements in an overlapping and redundant manner. The output sequences of recognized states from the output learning elements are collected and combined to provide a sequence of recognized patterns as an output of the probabilistic learning system. The reliability of the learning system is enhanced due to the overlapping and redundant nature in which the input objects are processed through the system and the time required to perform the system task is reduced through the use of parallel processing through the array. Each element of the array provides a signal correspoding to a rating of confidence in the recognized states and this rating of confidence is fed back to the input of the element to cause the element to learn the recognized states when the rating of confidence exceeds a predetermined threshold level. The rating of confidence is also provided to the inputs of prior elements in the array to cause the prior elements to learn their recognized states when the rating of confidence exceeds the predetermined threshold.
Denenberg, Jeffrey N., "Probabilistic Learning System (Sequential Pattern Recognition) U.S. Patent 4,599,693" (1986). Engineering Faculty Publications. 100.
Denenberg; Jeffrey N.. Probabilistic Learning System (Sequential Pattern Recognition) U.S. Patent 4,599,693 issued July, 1986