Pattern recognizer with independent feature learning

Claim 1

A device for recognizing and responding to physical patterns, comprising: (a) transducer means for producing an input signal representing a physical pattern in an environment; (b) a plurality of feature detectors responsive to said input signal, each feature detector having weight means for storing a representation of a preferred feature, for producing a feature activity signal representing degrees to which each of said preferred features exists in said input signal, and for producing a feature description signal representing said preferred features; (c) classifier means responsive to said feature activity signal, for producing an output signal representing a system action corresponding to said input signal; (d) effector means responsive to said output signal, for committing an action in said environment; (e) memory means responsive to said input signal, for approximately storing a representation of said input signal, and for producing a retrieval signal representing previously stored input signals; (f) assigner means responsive to said input signal and to said retrieval signal and to said feature description signal, for producing a part mapping signal representing a mapping between a plurality of parts and at least one responsible feature detector, such that each part corresponds to a likely feature of said input signal and of said previously stored input signals; (g) updater means responsive to said part mapping signal, for modifying each of said responsible feature detectors so as to make its preferred feature more similar to its assigned part; whereby the modification of each of said responsible feature detectors is largely independent of the modifications of the other feature detectors; whereby said device can be effectively trained with fewer physical pattern examples than a device having correlated feature training.

Claim 2

A device for recognizing and responding to physical patterns, comprising: (a) transducer means for producing an input signal representing a physical pattern in an environment; (b) a plurality of feature detectors responsive to said input signal, each feature detector having weight means for storing a representation of a preferred feature, for producing a feature activity signal representing degrees to which each of said preferred features exists in said input signal, and for producing a feature description signal representing said preferred features; (c) classifier means responsive to said feature activity signal, for producing an output signal representing a system action corresponding to said input signal; (d) effector means responsive to said output signal, for committing an action in said environment; (e) memory means responsive to said input signal, for approximately storing a representation of said input signal, and for producing a retrieval signal representing previously stored input signals; (f) assigner means responsive to said input signal and to said retrieval signal and to said feature description signal, for producing a part mapping signal representing a mapping between a plurality of parts and at least one responsible feature detector, such that each part corresponds to a likely feature of said input signal and of said previously stored input signals; (g) updater means responsive to said part mapping signal, for modifying each of said responsible feature detectors so as to make its preferred feature more similar to its assigned part; whereby the modification of each of said responsible feature detectors is largely independent of the modifications of the other feature detectors; whereby said device can be effectively trained with fewer physical pattern examples than a device having correlated feature training.

Claim 16

A method for creating a pattern recognition device, comprising the steps of: (a) providing transducer means for producing an input signal representing a physical pattern in an environment; (b) providing a plurality of feature detectors responsive to said input signal, each feature detector having weight means for storing a representation of a preferred feature, for producing a feature activity signal representing degrees to which each of said preferred features exists in said input signal, and for producing a feature description signal representing said preferred features; (c) providing classifier means responsive to said feature activity signal, for producing an output signal representing a system action corresponding to said input signal; (d) providing effector means responsive to said output signal, for committing an action in said environment; (e) providing memory means for approximately storing input patterns, and for producing a retrieval signal representing previously stored input patterns; (f) using said memory means to approximately store a sequence of comparison patterns; (g) providing a training pattern; (h) identifying a plurality of parts in said training pattern, such that each part corresponds to a likely feature of said training pattern and of said comparison patterns; (i) assigning each of said parts to a corresponding responsible feature detector; (j) modifying each of said responsible feature detectors so as to make its preferred feature substantially directly more similar to its assigned part; (k) training said feature detectors by repeating steps (g) through (j) on a significant portion of a training set until a training criterion is reached; whereby the modification of each of said responsible feature detectors is largely independent of the modifications of the other feature detectors; whereby said method allows effective creation of a pattern recognition device with fewer pattern presentations than a device having correlated feature training.

Claim 17

A method for creating a pattern recognition device, comprising the steps of: (a) providing transducer means for producing an input signal representing a physical pattern in an environment; (b) providing a plurality of feature detectors responsive to said input signal, each feature detector having weight means for storing a representation of a preferred feature, for producing a feature activity signal representing degrees to which each of said preferred features exists in said input signal, and for producing a feature description signal representing said preferred features; (c) providing classifier means responsive to said feature activity signal, for producing an output signal representing a system action corresponding to said input signal; (d) providing effector means responsive to said output signal, for committing an action in said environment; (e) providing memory means for approximately storing input patterns, and for producing a retrieval signal representing previously stored input patterns; (f) using said memory means to approximately store a sequence of comparison patterns; (g) providing a training pattern; (h) identifying a plurality of parts in said training pattern, such that each part corresponds to a likely feature of said training pattern and of said comparison patterns; (i) assigning each of said parts to a corresponding responsible feature detector; (j) modifying each of said responsible feature detectors so as to make its preferred feature substantially directly more similar to its assigned part; (k) training said feature detectors by repeating steps (g) through (j) on a significant portion of a training set until a training criterion is reached; whereby the modification of each of said responsible feature detectors is largely independent of the modifications of the other feature detectors; whereby said method allows effective creation of a pattern recognition device with fewer pattern presentations than a device having correlated feature training.

Claim 22

A device for recognizing and responding to physical patterns, comprising: (a) a transducer capable of producing an input signal representing a physical pattern in an environment; (b) a plurality of feature detectors each responsive to said input signal, each feature detector having weight storage capable of representing a preferred feature, each of said feature detectors being capable of producing a feature activity signal element representing a degree to which its preferred feature exists in said input signal, and being capable of producing a feature description signal element representing its preferred feature; (c) a classifier responsive to each said feature activity signal element, capable of producing an output signal representing a system action corresponding to said input signal; (d) an effector responsive to said output signal, capable of committing an action in said environment; (e) a memory responsive to said input signal, capable of approximately storing a representation of said input signal, and capable of producing a retrieval signal representing previously stored input signals; (f) an assigner responsive to said input signal and to said retrieval signal and to each of said feature description signal elements, capable of producing a part mapping signal representing a mapping between a plurality of parts and a plurality of responsible feature detectors, such that each part corresponds to a likely feature of said input signal and of said previously stored input signals, and such that each responsible feature detector has a high correspondence to its assigned part relative to the other feature detectors; (g) an updater responsive to said part mapping signal, capable of modifying each of said responsible feature detectors so as to make its preferred feature vector move substantially directly toward its assigned part vector; whereby the modification of each of said responsible feature detectors is largely independent of the modifications of the other feature detectors; whereby said device can be effectively trained with fewer physical pattern examples than a device having correlated feature training.

Claim 23

A device for recognizing and responding to physical patterns, comprising: (a) a transducer capable of producing an input signal representing a physical pattern in an environment; (b) a plurality of feature detectors each responsive to said input signal, each feature detector having weight storage capable of representing a preferred feature, each of said feature detectors being capable of producing a feature activity signal element representing a degree to which its preferred feature exists in said input signal, and being capable of producing a feature description signal element representing its preferred feature; (c) a classifier responsive to each said feature activity signal element, capable of producing an output signal representing a system action corresponding to said input signal; (d) an effector responsive to said output signal, capable of committing an action in said environment; (e) a memory responsive to said input signal, capable of approximately storing a representation of said input signal, and capable of producing a retrieval signal representing previously stored input signals; (f) an assigner responsive to said input signal and to said retrieval signal and to each of said feature description signal elements, capable of producing a part mapping signal representing a mapping between a plurality of parts and a plurality of responsible feature detectors, such that each part corresponds to a likely feature of said input signal and of said previously stored input signals, and such that each responsible feature detector has a high correspondence to its assigned part relative to the other feature detectors; (g) an updater responsive to said part mapping signal, capable of modifying each of said responsible feature detectors so as to make its preferred feature vector move substantially directly toward its assigned part vector; whereby the modification of each of said responsible feature detectors is largely independent of the modifications of the other feature detectors; whereby said device can be effectively trained with fewer physical pattern examples than a device having correlated feature training.