Design of equiripple linear phase FIR filters by feedback neural networks

A Hopfield-type neural network is proposed for the design of equiripple FIR digital filters. A weighted least-squares error function is minimized in an iterative fashion and weights are updated at the end of each iteration until the desired accuracy is achieved. The network is simulated and an example is included to show that this is an efficient way of solving the approximation problem and has a high potential for implementation in analog VLSI.