关键词: 泛函连接人工神经网络, 加权误差函数, 训练集选取规则, FIR滤波器

Abstract: To the neural network design method of Finite Impulse Response（FIR） filter，an improved algorithm of Functional Link Artificial Neural Network（FLANN） is advanced.It ameliorates learning effect by setting different weighted function values to control the learning rate of every sample，besides a training set selection rule is set down.Through training samples selected by the rule，a FIR filter with precisely controlled passband and stopband cut-off frequencies specifications can be designed.The algorithm overcomes the shortage of existing others which only can design a filter with passband cut-off frequency and can not precisely control arbitrary cut-off frequency.The result of simulation shows that the method proposed in this paper can satisfy the design requirement.

Key words: Functional Link Artificial Neural Networks（FLANN）, weighted error function, training set selection rules, FIR（Finite Impulse Response） filters