Patent ID: 7346497

Claim:
An artificial neural network classifier comprising: an input layer of one or more nodes to receive training data; an output layer L of one or more nodes to provide an actual output indicating a level of training of the artificial neural network classifier based on the training data; and at least a hidden layer of one or more nodes intermediate said input layer and said output layer, each node to receive input values via the input layer, each node to perform a transformation of the received input values based on a set of weights, each transformation to determine in part the actual output of output layer L, the set of weights to be updated based at least in part on an error function having an operator of the form ( 2 ⁢ t j - 1 ) n - 1 ⁢ ( t j - y j L ) n y j L ⁡ ( 1 - y j L ) , where y j L is an actual output at node j of output layer L, t j is a target output at the node j, and n is greater than or equal to two, wherein the updated set of weights is to be used in determining confidence level information for a feature vector.