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Matlab神经网络工具箱的应用简介，从原理到应用(Neural network toolbox)

matlab 分类器。。。。。。。。。。。。。。。。。。。。(matlab classifier. . . . . . . . . . . . . . . . . . . .)

单纯形算法，用于在线整定PID调节器参数(SPX caculation can be used in automatic PID controlled)

使用matlab进行数值分析时重要的参考资料，具体包含内容可以看英文描述(This text is written primarily for students/readers who have a good background of high school algebra, geometry, trigonometry, and the fundamentals of differential and integral calculus. This text includes the following chapters and appendices: . Introduction to MATLAB . Root Approximations . Sinusoids and Complex Numbers . Matrices and Determinants . Review of Differential Equations . Fourier, Taylor, and Maclaurin Series . Finite Differences and Interpolation . Linear and Parabolic Regression . Solution of Differential Equations by Numerical Methods . Integration by Numerical Methods . Difference Equations . Partial Fraction Expansion . The Gamma and Beta Functions . Orthogonal Functions and Matrix Factorizations . Bessel, Legendre, and Chebyshev Polynomials . Optimization Methods . Difference Equations in Discrete Time Systems . Introduction to Simulink . Ill Conditioned Matrices Each chapter contains numerous practical applications supplemented with detailed instructions for using )

This is the BER plot for QPSK..

识别线条的程序，自己的原创，能识别各种颜色的线条(Identify the lines of the program, their own originality, can identify a variety of color lines)

Image compression and dbxecompression using Discrete wavelet transform in matlab

fc-ae1553协议，光纤通道，总线应用(fc-ae1553 protocol, Fibre Channel, Bus Applications)

稳态kalman滤波算法仿真通式 本程序考虑线性离散时不变随机系统。系统模型为x(t+1)=fai*x(t)+gama*w(t) y(t)=H(t)*x(t)+v(t)。有6个参数：状态转移阵fai，输入噪声系数gama，观测阵H，输入 噪声方差Q，观测噪声方差R，观测y( Steady-state kalman filtering algorithm simulation program to consider the general form linear discrete time-invariant stochastic system. System model x (t+1) = fai* x (t)+ gama* w (t) y (t) = H (t)* x (t)+ v (t). There are six parameters: state transition matrix fai, input noise figure gama, observation matrix H, enter noise variance Q, observation noise variance R, observation y)

this is the modulation techniques in matlab