Patent ID: 7286699

Claim:
A pattern recognition system, comprising: a preprocessing component that receives an input and provides an output pattern; at least one convolutional layer that receives the output pattern from the preprocessing component, the convolutional layer comprising a plurality of feature maps, the feature map including trainable parameters, the at least one convolutional layer providing outputs associated with features extracted from the output pattern; and, at least one fully connected layer that receives outputs from the at least one convolutional layer, the at least one fully connected layer classifying the features extracted by the at least one convolutional layer, the at least one fully connected layer providing a plurality of outputs, the output comprising a probability associated with a class, the pattern recognition system trained utilizing cross entropy error minimization based at least in part, upon the equation E = - ∑ n ⁢ ⁢ ∑ k = 1 c ⁢ ⁢ { t k n ⁢ ln ⁡ ( y k n ) + ( 1 - t k n ) ⁢ ln ⁡ ( 1 - y k n ) } where E is the energy to be minimized, n indexes a pattern, t is the target value, y k n is the pattern recognition output on unit k for pattern n, and k indexes the classes.