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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
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一个MIMO 2*2系统的误码率仿真,收端采用MMSE-SIC检测方式-computing the BER for BPSK modulation in a Rayleigh fading channel with 2 Tx, 2Rx MIMO channel Minimum Mean Square Error Equalization with Successive Interference Cancellation
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chan算法，利用TDOA参数实现定位功能，是一种很经典的算法-chan algorithm parameters using TDOA positioning function, is a classic algorithm
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MATLAB code on linear minimum mean square error (LMMSE) estimation and its application to the problem of channel equalization in digital communication systems.
amr amin: code on the application of channel equalization in digital communication sys
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MATLAB code on linear minimum mean square error (LMMSE) estimation and its application to the problem of channel equalization in digital communication systems.
amr amin: code on the application of channel equalization in digital communication sys
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MATLAB code on linear minimum mean square error (LMMSE) estimation and its application to the problem of channel equalization in digital communication systems.
amr amin: code on the application of channel equalization in digital communication sys
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MATLAB code on linear minimum mean square error (LMMSE) estimation and its application to the problem of channel equalization in digital communication systems.
amr amin: code on the application of channel equalization in digital communication sys
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MATLAB code on linear minimum mean square error (LMMSE) estimation and its application to the problem of channel equalization in digital communication systems.
amr amin: code on the application of channel equalization in digital communication sys
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1.原始信号A，通过信道受噪声污染后的信号q，然后分别经过均衡器ZF（MMSE）得到信号U，可以画出U的分布图 2.分别应用LMS,SATO,CMA算法得到U。（其中包括最佳延迟、均方误差的计算）所有结果均以图像形式显示。-1. The original signal A, subject to noise pollution through the channel after the signal q, and then through the equalizer, respectively
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Inter-symbol interference if not taken care off may
cause severe error at the receiver and the detection of signal becomes
difficult. An adaptive equalizer employing Recursive Least Squares
algorithm can be a good compensation for the ISI probl
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Calculate the Mean Square Error (MSE) and the Peak Signal to Noise Ratio (PSNR) for different JPEG compression ratios.
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基于lms算法的干扰自适应抵消LMS算法是基于最陡下降法的统计估计的最小均方值算法，令误差的均方值达到最小时的抽头系数的值即为最优解。LMS算法抽头系数w的变化方向为代价方程的负梯度方向。-Lms algorithm based on adaptive interference cancellation algorithm is the LMS steepest descent method based on statistical estimation of the least mean sq
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层空时码有三种普遍的检测算法：最大似然（Maximum Likelihood ,ML）检测算法、迫零（zero forcing ,ZF）检测算法、最小均方误差（Minimum Mean Squared Error,MMSE）检测算法。-There are three layers in general space-time code detection algorithms: maximum likelihood (Maximum Likelihood, ML) detection algori
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A multiple-input multiple-output (MIMO) communication system combined with the orthogonal frequency division multiplexing (OFDM) modulation technique can achieve reliable
high data rate transmission over broadband wireless channels. Channel state i
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LS (Least Square) & LMMSE (Minimum Mean Square Error)
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Noise cancellation with Minimum Mean Square Error via LMS algorthim in Matlab simulation software
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由于通常的通信信道的冲激响应的稀疏性，使得NLMS算法的收敛速度还有待提高。所以，近年来，有学者提出了成比例的归一化的均方误差算法(PNLMS)。PNLMS在自适应过程的开始阶段有着很快的收敛的速度，但是迭代过程越往后，收敛速度越慢。于是，众多学者提出了许多的改进算法。本程序是通过matlab仿真对近年来流行的PNLMS,IPNLMS,MPNLMS等算法进行的仿真程序-As usual communication channel impulse response sparse, making t
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minimum mean square error implementation in matlab for a certain channel response in a noisy channel
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this matlab code is a least mean square error method for ellipse fitting that can fit the best ellipse in an image-this matlab code is a least mean square error method for ellipse fitting that can fit the best ellipse in an image
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BP学习算法逼近墨西哥草帽函数
在Windows环境中利用Matlab实现BP学习算法在达到期望均方误差最小的情况下正确表达墨西哥草帽函数。
实验目的：1.理解BP神经网络结构模型，初步了解BP网络的用途。
2.学习BP学习算法，掌握误差往回传播网络的构建思想。
3.能够正确使用BP学习算法表达墨西哥草帽函数。
-BP learning algorithm Mexican hat function approximation
BP learning algorithm
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