Hybrid Filter Banks Optimization Design Using Regularization  Weighted Least Squares Solving

 The ill-posed problems caused by analogy analysis filters realization error and digital synthesis filter banks fitting error for limited order，which usually impact the reconstruction performance of the hybrid filter banks (HFB). A novel regularization criterion for designing IIRtype synthesis filter banks based on weighted least squares (WLS) are proposed， which satisfying near perfect reconstruction. Based on the second-order-statistics， the disturbers which caused by realization and random noise can be restrained by means of the WLS. So the weighted mean squares of synthesis filter banks frequency responses can be Minimize. The regularization criterion can overcome the instability solution of WLS effectively. A novel approach for designing IIR-type filters are given， which can optimize the coefficients of filters by means of the regularization method and reduce the implement error. This approach can also be used in designing over-sampling HFB. The simulation results show that this approach can improve the system robust and reconstruction performance significantly.