초록 ▼

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 a

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.

대표청구항 ▼

A probabilistic learning system that receives sequential input data and outputs sequences of recognized patterns, comprising: an array of interconnected probabilistic learning elements that receives sequences of objects and output sequences of recognized states, said array of learning elements being

A probabilistic learning system that receives sequential input data and outputs sequences of recognized patterns, comprising: an array of interconnected probabilistic learning elements that receives sequences of objects and output sequences of recognized states, said array of learning elements being interconnected to have a number of input learning elements and a number of output learning elements the sequences of recognized states from predetermined learning elements being combined to form objects to be received by other learning elements of the array; means for receiving and partitioning the input data between the input learning elements of the array in an overlapping and redundant manner, whereby the partitioned input data become objects provided to the input learning elements; and means for collecting and combining the recognized state sequences from the output learning elements of the array and for providing a sequence of recognized patterns as an output of the probabilistic learning system, whereby the reliability of the learning system is enhanced due to the overlapping and redundant nature in which the input data is processed through the system and the time required to perform the system task is reduced through the use of parallel processing through the array.