work

很好用的FastICA工具箱，以及使用攻略，非常容易入手学习。(Good use of FastICA toolbox, and the use of the Raiders, very easy to start learning.)

example qpsk modulation

利用蚁群算法的改进算法实现图像分割，并与传统蚁群算法作比较(The improved ant colony algorithm is used to realize image segmentation and compared with the traditional ant colony algorithm.)

说明：  MATLAB/simulink光伏电池建模！！！！(Photovoltaic cell modeling)

说明：  6.78M class e 无线充电仿真(6.78M class e wireless charging simulation)

mfcc.m matlab frquency an d formant method

LMS三角定位迭代加权算法 LMS三角定位迭代加权算法 LMS三角定位迭代加权算法(LMS triangulation iterative weighting algorithm LMS triangulation iterative weighting algorithm LMS triangulation iterative weighting algorithm)

MATLAB 牛顿下山法的一个小程序，原理就不详细说了。因牛顿迭代法受初值选取的限制，为防止迭代发散，对迭代过程再附加一项要求:|f(x(k+1))|<|f(x(k))|,将牛顿法迭代的结果:x(k+1) =x(k)-f(x(k))/f (x(k))和前一近似值x(k)适当加权平均做为新的改进值:x(k+1)=u*x(k+1) +(1-u)*x(k),其中u(0<> 迭代时u取1开始，逐次减半计算，直至附加要求符合为止。实例计算中x(k)=x(0)不变，只更新u和x(k+1)，直至:|f(x(k+1))|<|f(x(k))|（即|f(x(1))|<|f(x(0))|)，然后更新下山因子为u=1,继续以牛顿法迭代。(MATLAB Newton-down a small program, the principle is not explained in detail. Newton iteration by the initial value of the selected limit, in order to prevent additional iterative divergence, the iterative process a request: | f (x (k+1)) | < | f (x (k)) | Newton iteration Results: x (k+1) ' = X (k)-f (x (k))/f' (x (k)) and a previous approximation x (k), appropriately weighted average as a new improved value: x (k+1 ) = u* x (k+1) ' + (1-u)* x (k), where u (0 < u> iteration take successive calculated at 50 until the additional requirements found so far. examples of calculation of X ( k) = x (0) unchanged profile u and x (k+1, hungry) until: | f (x (k+1)) | < | f (x (k)) | (i.e. | f (x (1)) | < | f (x (0)) |), then profile downhill factor for u = 1, to continue to Newton iteration.)

kalman滤波算法程序是matlab的程序(An improved adaptive filter state estimation, the effect is definitely a good thing, is to use MATLAB prepared directly in matlab run will be able to see the effect of a perfect filter, adaptive algorithm is sage-husa algorithm, a more traditional filter machine has greatly improved)

零延时卷积算法实现，基于fft变换。Efficient Convolution Without Latency by William G. Gardner(It is well known that a block FFT implementation of convolution is vastly more efficient than the direct form FIR filter. Unfortunately, block processing incurs significant input/output latency which is undesirable for real-time applications. A hybrid method is proposed for doing convolution by combining direct form and block FFT processing. The result is a zero latency convolver that performs significantly better than direct form methods.)