PATTERN RECOGNIZER WITH INDEPENDENT FEATURE LEARNING

摘要

A pattern recognition device having modifiable feature detectors (28) which respond to a transduced input signal (26) and communicate a feature activity signal (30) to allow classification and an appropriate output action (70). A memory (40) stores a set of comparison patterns, and is used by an assigner (66) to find likely features, or parts, in the current input signal (26). Each part is assigned to a feature detector (28[m]) judged to be responsible for it. An updater (42) modifies each responsible feature detector (28[m]) so as to make its preferred feature more similar to its assigned part. The modification embodies a strong constraint on the feature learning process, in particular an assumption that the ideal features for describing the pattern domain occur independently. This constraint allows improved learning speed and potentially improved scaling properties. A first preferred embodiment uses a group of noisy-OR type neural networks (50) to implement the feature detectors (28) and memory (40), and to obtain the parts by a soft segmentation of the current input signal (26). A second preferred embodiment maintains a lossless memory (40) separate from the feature detectors (28), and the parts consist of differences between the current input signal (26) and comparison patterns stored in the memory (40).