基于状态转移法的正弦基神经网络滤波器设计

发布时间：2018-03-19 00:25

本文选题：状态转移算法　切入点：正弦基函数　出处：《计算机仿真》2017年02期 　论文类型：期刊论文

【摘要】：为了改善常用滤波器设计方法存在的不足,用一组正弦基函数神经网络线性组合逼近理想滤波器的振幅响应,用状态转移算法优化基函数神经网络权值,使得实际滤波器的幅度响应逼近理想滤波器的幅度响应,建立了基于状态转移算法的正弦基函数神经网络滤波器设计模型。与窗函数法设计的滤波器对比,上述模型具有更好的性能,实验结果表明,状态转移算法优化权值的方法,克服了传统基函数神经网络模型权值不易确定,收敛速度慢等缺点。
[Abstract]:In order to improve the shortcomings of the common filter design methods, a group of sinusoidal basis function neural networks are used to approximate the amplitude response of the ideal filter, and the state transfer algorithm is used to optimize the weight of the basis function neural network. The amplitude response of the actual filter approximates the amplitude response of the ideal filter. A sinusoidal basis function neural network filter design model based on the state transfer algorithm is established, which is compared with the filter designed by the window function method. The experimental results show that the state transfer algorithm can optimize the weights of the model, which overcomes the disadvantages of the traditional basis function neural network model, such as the difficulty to determine the weights and the slow convergence speed.
【作者单位】：新疆大学网络与信息技术中心;
【分类号】：TN713

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