METHOD AND SYSTEM FOR IMPROVING PERFORMANCE OF AN ARTIFICIAL NEURAL NETWORK

This disclosure relates to method and system for improving performance of an artificial neural network (ANN). The method may include receiving a weight matrix comprising an original weight of each neural node in each layer of the ANN. For each unique combination of at least two neural nodes in each layer, the method may further include determining a relative advantage value for one of the at least two neural nodes in a given layer with respect to remaining of the at least two neural nodes in the given layer based on actual inputs and standard inputs to the at least two neural nodes, and determining a modified weight of each of the at least two neural nodes based on the relative advantage value. The method may further include executing an elimination decision for each neural node in each layer based on a corresponding final modified weight, and updating the weight matrix based on the final modified weight of each remaining neural node in each layer. The final modified weight of a given neural node in a given layer is the modified weight of the given neural node upon exhausting each unique combination of the at least two neural nodes in the given layer.