1. A pattern recognition system, comprising: at least one convolutional layer that receives a non-temporal input pattern, the convolutional layer comprising a plurality of feature maps, the feature map receiving at least a portion of the non-temporal input pattern, the feature map including trainable parameters, the at least one convolutional layer providing outputs associated with features extracted from the non-temporal input 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.