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Adaptive Filtering Primer with MATLAB - Poularikas and Ramadan

model LPV the DFIG in matlab

说明：  MATLAB 代码 第1章 BP神经网络的数据分类——语音特征信号分类 第2章 BP神经网络的非线性系统建模——非线性函数拟合 第3章 遗传算法优化BP神经网络——非线性函数拟合 第4章 神经网络遗传算法函数极值寻优——非线性函数极值寻优 第5章 基于BP_Adaboost的强分类器设计——公司财务预警建模 第6章 PID神经元网络解耦控制算法——多变量系统控制 第7章 RBF网络的回归--非线性函数回归的实现 ....等58章(MATLAB code The first chapter is BP neural network data classification -- speech characteristic signal classification The second chapter is the nonlinear system modeling of BP neural network nonlinear function fitting The third chapter, genetic algorithm optimization BP neural network - nonlinear function fitting The fourth chapter, neural network, genetic algorithm, function extreme value optimization nonlinear function extremum seeking The fifth chapter is based on BP_Adaboost's strong classifier design -- the company financial early-warning model The sixth chapter is PID neural network decoupling control algorithm multivariable system control The seventh chapter is the regression of RBF network the realization of nonlinear function regression .........the last is 58 chapters)

Multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) is very sensitive to the carrier frequency offset (CFO), which not only affects the channel estimation but also the selection of a minimum error probability based precoder for peak-to-average power ratio (PAPR) reduction such that the system performance will degrade. This paper presents the joint scheme of CFO) and channel estimation in the MIMO-OFDM systems with the minimum error probability based precoder for reducing PAPR. We provide the solution to eliminate the effects of ICI due to CFO mismatch for OFDM with space frequency block codes and spatial multiplexing, drive a generalized linear model and propose a non-iterative reduced complexity model.

MODELING AND SIMULATION OF IEEE 14 BUS SYSTEM WITH FACTS Controller

说明：  比较详细的蚁群算法matlab程序，主要功能解决旅行商问题(Ant colony algorithm in more detail matlab program, the main function of Traveling Salesman Problem)

应用matlab，仿真雪花飘飞，非常的逼真直观(Application of Matlab simulation snowy, very realistic and intuitive)

extends Activity Instrumentation Test Case2.

the equivalent of Zhou Wang s SSIM matlab code //with K1 = 0.01, K2 = 0.03 and windows = ones(8) since this enables a fast implementation using summed area tables. //the measure is described in "Image quality assessment: From error measurement to structural similarity" //was originally adapted from the matlab code for the universal image quality index

matlab生成随机数，uinform产生一组[0，1]分布的随机数，riddling产生一个N(0,1)正态分布随机数，normal产生n个N(a,b)正态分布随机数。(Use matlab to generate random numbers, uinform produce a set of [0,1] random number distribution, riddling produce a N (0,1) normally distributed random numbers, normal generate n N (a, b) normally distributed random numbers.)