This document presents an FPGA implementation of a genetic algorithm for identifying parameters of linear and nonlinear auto regressive moving average (ARMA) models. The genetic algorithm uses 6-bit fixed-point arithmetic to reduce hardware costs. Experimental results show the design can accurately identify parameters for both linear and nonlinear models using low FPGA resources.