双通带数字滤波器优化设计研究

提出了一种基于BP算法的正弦基函数神经网络模型及算法的收敛条件,研究了该神经网络算法与FIR线性相位滤波器幅频特性的关系,给出了高阶双通带滤波器的优化设计实例.计算机仿真结果表明,该神经网络算法不仅是有效的,而且是高效的.与传统的窗口函数法和雷米兹优化设计方法相比,其优化设计方法不需要计算矩阵的逆,因而克服了雷米兹优化设计方法求高阶矩阵逆的困难.

Study on Optimal Design of Digital Filters with Double-Band-Pass

This paper presents a model of cosine basis functions neural network based on BP algorithm,discusses the relation between the algorithm of neural network and amplitude-frequency characteristic about the linear phase FIR filter,introduces the convergence condition of neural network algorithm,and studies the optimal design example about the high-order FIR double-band-pass filters.The simulation result shows that the neural-network algorithm is not only effective but also with high efficiency.Compared with the traditional methods of window functions and Remez optimal algorithm,the optimum algorithm,the optimum design method in the paper need not compute inverse matrix,thus overcoming the difficulty to compute high-order inverse matrix in Remez optimal design method.