Abstract: A method including, at a processor, obtaining an input to be classified, training a neural network, and classifying the input using the trained neural network. The training of the neural network being done in a feed-forward manner based on a plurality of sample inputs and sample classifications. Each of the sample classifications is associated with one of the plurality of sample inputs. The training includes, for each of a plurality of layers in the neural network, selecting values for a weight matrix, parameters for a plurality of activation unit functions, and a plurality of linear filter parameters. The classifying the input using the trained neural network is based on the weight matrix, the parameters for the plurality of activation unit functions, and the plurality of linear filter parameters for each of the plurality of layers.