1. A classification method for classifying an input into one of a plurality of possible outputs, comprising the steps of: (a) comparing information representative of said input to a neuron, wherein said neuron comprises a boundary defined by two or more neuron axes, wherein the length of at least one of said two or more neuron axes differs from the length of at least one other of said two or more neuron axes; and (b) selecting one of said possible outputs as corresponding to said input in accordance with the comparison of step (a), wherein: step (a) comprises the step of comparing information representative of said input to a plurality of neurons; each neuron of said plurality of neurons comprises a boundary defined by two or more neuron axes; the length of at least one of said two or more neuron axes differs from the length of at least one other of said two or more neuron axes; said information representative of said input comprises a feature vector; step (a) further comprises the step of selecting each neuron that encompasses said feature vector; and step (b) further comprises the steps of: (i) determining a first number that is a function of the number of said selected neurons that are associated with a first possible output of said plurality of possible outputs; (ii) de. termining a second number that is a function of the number of said selected neurons that are associated with a second possible output of said plurality of possible outputs; and (iii) if said first number is greater than said second number then determining that said input does not correspond to said second possible output, else if said second number is greater than said first number then determining that said input does not correspond to said first possible output.