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Description: 神经网络原理 Simon Haykin
基本涵盖了神经网络的许多基础部分和重要方面。像Back Propagation， Radial-Basis Function，Self-Organizing Maps，以及single neuron中的Hebbian Learning, Competitive Learning和LMS Learning。 -Neural network theory Simon Haykin covering the basic part of the neural network and the many important aspects. Like Back Propagation, Radial-Basis Function, Self-Organizing Maps, and the single neuron in the Hebbian Learning, Competitive Learning and LMS Learning.
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Description: 一种新的变步长LMS自适应滤波算法，本文通过建立步长因子L与误差信号之间的非线性函数关系,提出了一种新的变步长LMS(Least
Mean Square)算法.该算法具有初始阶段和未知系统时变阶段步长自动增大而稳态时步长很小的特点,且克服了S函
数变步长LMS算法(简称SVSLMS算法)在自适应稳态阶段L(n)取值偏大的缺陷.理论分析和计算机仿真结果表明
该算法的性能优于SVSLMS算法.
-By building a nonlinear function relationship betweenLand the error signal,this paper
presents a novel variable step size LMS(Least Mean Square)adaptive filtering algorithm.The step size of
this algorithm increases automaticly at the beginning of this algorithm or when unknown system is chan-
ging with time,and it would be smaller during the steady state.This algorithm avoid the shortage of chan-
ging step size of SVSLMS,variable step size LMS based on Sigmoid function,in the process of the adaptive
steady state.The performance of this paper algorithm is better than that of SVSLMS with the theoretical
analysis and computer simulations.
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Size: 69632 |
Author: Johnson |
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Description: 自适应滤波器LMS算法包括SIMULINK模型及S函数的编写-LMS adaptive filter algorithm, including the preparation of the SIMULINK model and S function
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Size: 11264 |
Author: 赵伟静 |
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Description: 通过设计一个二阶加权系数自适应横向FIR滤波器，对一个加随机噪声的正弦信号实现滤波。
具体设计方案为：
1，生成标准正弦信号S
2，生成等长的随机信号N
3，生成加随机噪声的正弦信号X
4，X通过参数可调数字滤波器，输出Y
5，Y与参考信号作差得到误差E
6，E通过自适应算法调整权值W
7，用LMS算法处理噪声干扰的信号，最终实现滤波器功能(A two order weighted coefficient adaptive transverse FIR filter is designed to filter a sinusoidal signal with random noise.
The specific design scheme is as follows:
1, generating a standard sinusoidal signal S
2, generating an equal length random signal N
3, generating a sinusoidal signal X with random noise
4, X can adjust the digital filter by parameter and output Y
5, the difference between the Y and the reference signal is E
6, E adjusts the weight W through the adaptive algorithm
7, the LMS algorithm is used to deal with the noise interference signal, and the filter function is finally realized.)
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Size: 1605632 |
Author: 硕35687491 |
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