Abstract:A novel algorithm is proposed based on the genetic theory, which has global optimum searching characteristic. Meanwhile, considering its computational cost, decimal code, not binary one is used in operation of the operators. Moreover, a modified adaptive weights training algorithm is also used to resolve the weights fluctuant problem in stable range. Numerical simulations demonstrate that tlie genetic algorithm can converge at the global extremum quickly, and that weights estimation with the modified adaptive weights training algorithm have a more stable range, and the filtering performance has been improved obviously.