Method and apparatus for adaptive classification
AssigneeNestor, Inc.
InventorsMichael T. Glier, Linda I. Mensinger Nunez, Christopher L. Scofield
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Abstract
A neural network and method for pipeline operation within a neural network which permits rapid classification of input vectors provided thereto is disclosed. In a training mode, a plurality of training input features are presented to the neural network and distances between the plurality of training features and a plurality of prototype weight values are concurrently computed. In response to an indication of a last training epoch count values for each of the prototype weight values are stored in a memory to thereby allow the neural network to operate in a probabilistic classification mode.
Claims4
A method of training a neural network having an input layer, a middle layer and an output layer, comprising the steps of:
- (a) presenting an input vector having a plurality of training features to the neural network;
- (b) computing distances between a plurality of said training features and a plurality of prototype weight values;
- (c) generating, for each prototype weight value, a count value corresponding to a number of occurrences of an input vector that falls within a region of influence of a particular prototype;
- (d) repeating steps (a)-(c) until the neural network provides an indication of a last training epoch;
- and
- (e) in response to the indication of the last training epoch, storing, in a memory, the count value for each of the prototype weight values.
Dependencies are inferred from the claim text.