神经网络在4型FIR滤波器的优化设计研究

Optimized Design of the Type-four FIR Filter Based on Neural Networks with Sine Basis Functions

本文详细讨论了4型线性相位滤波器幅频特性与正弦基神经网络算法间的关系,提出并证明了该算法的收敛定理,给出了FIR高通滤波器和FIR带通滤波器优化设计实例。计算机仿真结果表明,该算法在FIR高通滤波器和带通滤波器的有效性和优异性能。

The relationship between the amplitude-frequency characteristic of linear phase type-four FIR filters and the algorithm of the neural networks based on sine basis functions is discussed in detail. Related convergence theorem is deduced. Examples of optimized design of type-four FIR filters are also introduced. Simulation results show that the proposed neural network is effective for the design of FIR high-pass and band-pass filters.