fractal-array

两带随机参量的复指数信号之和，用MVDR进行信号频率谱估计。(Two of the sum of complex exponential signal with random parameters, the MVDR is used to estimate signal frequency spectrum.)

Pisarenko谐波分解算法,wolf 方法计算李雅普诺夫指数,本科毕设要求参见标准测试模型。( Pisarenko harmonic decomposition algorithm, wolf calculated Lyapunov exponent, Undergraduate complete set requirements refer to the standard test models.)

利用MATLAB编写的神经网络源程序，很实用(using MATLAB prepared by the neural network program, a very practical)

从网上学习的一种对三个运动目标跟踪的多目标跟踪算法，采用卡尔曼滤波方法进行预测。效果还不错。(From an e-learning to track moving targets on the three multi-target tracking algorithm using Kalman filtering method to predict. Results were pretty good.)

SFASEDV DFV SV DF FEVE EF F VD EF E EWCF

MATLAB几何变换，可以方便了解到所变换的几种形式(MATLAB geometric transformations, you can easily understand the transformation of several forms)

用matlab采用双尺度方程求解小波基函数的方法 构造小波基(wavelet_function)

完整的makay的LDPC码生成和译码的程序。(Complete makay the LDPC code generation and decoding procedures.)

RNNSIM ver. 1.0 is a program with an intercative graphical user interface (GUI) that runs under MATLAB ver. 5.0 or higher. The program can be used in training and testing the Random Neural Network(RNN) models. This version (ver. 1.0) implements only the 3 layer feed forward RNN model. In the next versions, the multi hidden layers and the recurrent RNN models can be implemented. To obtain faster training, the training section can be written as a MEX file and invoked from the GUI. If you have the m files in the directory rnnsim for example, then you can run the program following the next steps: 1- run MATLAB as usual 2- from the MATLAB command window, write cd rnnsim 3- from the MATLAB command window, write rnnsim

数字图像处理与机器视觉-visual C++与matlab实现,第8章配套源程序(Digital image processing and machine vision of-visual C++ and MATLAB, the 8th chapter matching source)