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遗传算法TDOA解决
- 用遗传算法解决通信中的TDOA问题 文件名 program 完成功能 求出在进行account_test次的试验中每一次的最优染色体，并且求出均值MV，和均方误差MSE 文件名 definition_constant( ) 完成功能 对各个常量试验参数进行设定 文件名 main_program 完成功能 完成一次试验的计算 文件名 all_Noise 完成功能 计算TDOA值（由基站所测量的TDOA（受到噪声的干扰）) 文件名 gen_ini_pop_
Volterra_luzhenbo5
- 更新说明： 此版本在版本1、2的基础上做了2点重大改进 1、改进了PhaSpa2VoltCoef函数算法，使得现算法的运行速度约是原算法的4倍 2、改进了volterra_train_lu函数算法，使得相对均方误差提高了约1000倍，新算法不再需要对样本做归一化处理-Update : This version of the 1,2 version on the basis of a 2:00 a significant improvement, improved PhaSpa2Vol
bp-matlab
- BP神经网络算法的matlab代码，本程序根据训练好的网络文件ANN.mat预测新的数据文件，得到均方误差，并画出预测数据和原数据的对比图。希望有用-BP neural network algorithm Matlab code, the procedures under the trained network file ANN.mat anticipating new data files, be mean square error, paint and forecast data and t
nnforcast
- 本程序根据训练好的网络文件ANN.mat预测新的数据文件，得到均方误差，并画出预测数据和原数据的对比图。此程序运用到了很多Matlab编程中常用到的表达方式，还有一些神经网络编程的基本概念的表达，如归一化的表达。希望能对别人有所帮助.-the procedures under the trained network file ANN.mat anticipating new data files, to be mean-square error. and the mapping out of t
BPneuralnetworksouce
- BP神经网络c++源程序 采用3个隐层减少误差 均方误差程度可以接受-BP Network c source used three hidden layers reduce the error mean square error acceptable level
LMS-MATLAB
- LMS-MATLAB最小均方算法的Matlab源程序,模式识别中的分类器-LMS-MATLAB least-mean-square algorithm of Matlab source code, Pattern Recognition Classifier
An_Adaptive_Transverse_filter_using_LMS_algorithm.
- 本文件介绍采用最小均方算法的自适应横向滤波器,pdf文件内含有相应的MATLAB程序及仿真结果等。-This document describes the use of least mean square adaptive transversal filter algorithm, pdf file containing the appropriate procedures and simulation results of MATLAB.
bpprogramming
- 这个程序根据训练好的网络文件ANN.mat预测新的数据文件，得到均方误差，并画出预测数据和原数据的对比图。此程序运用到了很多Matlab编程中常用到的表达方式，还有一些神经网络编程的基本概念的表达，如归一化的表达。希望能对大家有所帮助-This program the trained network file ANN.mat predict new data file, get the mean square error, and forecast data and the original d
fuzzyanfis
- TS的模糊神经网络程序，包括数据对比输出，网络均方差输出对比，隶属度函数对比-TS fuzzy neural network program, including the comparison of the data output, the network mean square output contrast, comparison of membership functions
equality_constraints_of_uncertain_systems_filterin
- 研究了一类离散不确定系统中存在等式约束时的最优滤波问题，在均方误差最小的意义下利用卡尔曼滤波给出了最优解。与传统的不确定滤波结果相比，从理论证明了利用更多信息的约束滤波的估计误差协方差的迹更小。-A class of discrete uncertain systems exist in the optimal filter when the equality constraint problem, the minimum mean square error in the sense of Ka
LMS-code
- 给出一种LMS算法，即最小均方算法，采用一种特殊的梯度估值，它的显著特点是它的简单性，不需要计算相关函数，也不需要矩阵求逆运算。-Gives a LMS algorithm, least mean square algorithm, using a special gradient estimates, and its distinctive feature is its simplicity, need not calculate the correlation function, does
x
- This derivation of the normalised least mean square algorithm is based on Farhang- Boroujeny 1999, pp.172-175, and Diniz 1997, pp 150-3. To derive the NLMS algorithm we consider the standard LMS recursion, for which we select a variable step size
LMS
- 基于神经网络最小均方误差的分类算法，根据LMS准则来对数据进行分类-Based on minimum mean square error of neural network classification algorithm based on LMS criteria to classify the data
using-adaptive-chebyshev
- 提出了一种基于自适应 Chebyshev 多项式神经网络(ACNN)的 Logistic 混沌系统控制算法。该算法采用 Chebyshev 正交多项式作为神经网络的激励函数, 构建 Logistic 混沌系统的预测与控制模型。为了保证算法的稳定性, 提出和证明了收敛定 理, 并利用自适应学习率算法提高神经网络的学习效率和收敛速度。通过采用自适应 Chebyshev 神经网络直接学习 Logistic 混 沌系统的动态特性, 并对系统实施目标函数控制。实验仿真结果表明, 该算法在 L
bp-code
- 利用BP神经网络进行数据预测，得到均方误差，并画出预测数据和原数据的对比图。-BP neural network for data, forecasts, get the mean square error, and forecast data and raw data to draw the comparison chart.
A-hybrid-least-squares
- A hybrid least squares support vector machines and GMDH approach for river fl ow forecasting-This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares supp
10.1.1.11.5905
- This paper compares performance of nite impulse response (FIR) adaptive linear equalizers based on the recursive least-squares (RLS) and least mean square(LMS) algorithms in nonstationary uncorrelated scattering wireless channels. Simulation resul
SGA
- 用标准的遗传算法优化低通数字滤波器的参数，采用的方法是最小均方误差法，得到较为理想的滤波器的传递函数的系数。-Genetic algorithm using standard low-pass digital filter, the method used is the minimum mean square error method to obtain the ideal filter transfer function coefficients.
matlab-for-neural-network
- BPnet.m、GRNNnet、RBFnet分别为BP神经网络、GRNN神经网络、RBF神经网络用于预报模型的代码，其中给出预报的精度指标：合格率、确定性系数、均方根误差-BPnet.m, GRNNnet, RBFnet were BP neural network, GRNN neural network, RBF neural network for forecasting model code, which gives the prediction accuracy indicators:
LMS_NLMS_RLS
- LMS算法和NLMS算法以及RLS算法演示程序-Lest Mean Square (LMS) Algorithm Recursive Least Square (RLS) Algorithm Normalized LMS (NLMS) Algorithm Demo