Optimum Design of 2-D Linear-Phase FIR Digital Filters
二维线性相位FIR数字滤波器的优化设计

This paper provides a new design approach based on a Neural Networks Algorithm(NNA).According to the amplitude-frequency response characteristics of 2-D FIR linear-phase filters,the NNA is established.Using the NNA,the designed filter coefficients can be obtained from the specified amplitude-frequency responses.To ensure stability of the NNA,the convergence theorem of the NNA is presented and proved.Two examples including circularly-symmetric and quadrately-symmetric 2-D lowpass linear-phase FIR filtsrs are also given to illustrate the effectiveness of the NNA-based design approach,and the results show that the ripple is considerably small in passband and in stopband,and the NNA-based method is of strong stability and requires significantly little amount of computations.Therefore,the optimal design approach is effective and excellent in the design field of 2-D linear phase FIR digital filters.