matlab

Hopfiel Matlabe codes

假设一个接收到的信号为：x(t)=s(t)+n(t), 其中s(t)=A*cos(wt+a), 已知信号的频率w=1KHz， 而信号的幅度和相位未知，n(t)是一个服从N(0,1)分布的白噪声。为了利用计算机对信号进行处理， 将信号按10KHz的频率进行采样。 通过对x(t)进行LMS自适应信号处理，从接收信号中滤出有用信号s(t). 在未知信号频率的情况下，通过对x(t)进行LMS自适应信号处理，从接收信号中滤出有用信号s(t). (Assuming a received signal: x (t) = s (t)+ n (t), one of s (t) = A* cos (wt+ a), the known frequency signal w = 1KHz, And the signal amplitude and phase of the unknown, n (t) is a subject to N (0,1) the distribution of white noise. The use of computers in order to deal with the signal, The signal by sampling frequency of 10KHz. Of x (t) for LMS adaptive signal processing, filtering from the received signal in the useful signal s (t). Frequency signals in unknown circumstances, the adoption of x (t) for LMS adaptive signal processing, filtering from the received signal in the useful signal s (t).)

Wireless communication

学习MATLAB的参考资料，对于初学者，可以参考里面的讲解实例。(Learning MATLAB reference, for beginners, can explain the instance reference inside.)

利用 OptiSystem 设计光通信系统,有很多有关光子学仿真实验的详细介绍，对于通信学习有比较好的借鉴。(OptiSystem design optical communication systems use, there are many details about photonics simulation experiments, learning to communicate better reference.)

svm参数优化方法，网格算法，可修改迭代次数等参数(svm parameter optimization method, the mesh algorithms can modify parameters such as the number of iterations)

Matlab数字信号处理与应用源代码, 包含的实例所使用的源程序清单，文件夹第3章～第7章分别包括各章节内的实例源程序。 (Digital signal processing and application of Matlab source code that contains an instance of the use of source lists, folders, Chapter 3 ~ Chapter 7, respectively, including source code examples within the chapters.)

code for maximum likelyhood in matlab

matlab环境下编成的用于回归的支持向量机源程序(svm for regression)

1、系统仅处于训练状态。训练序列为2cos(2π×f1×n/fs)， 干扰为sin(2π×f2×n/fs)；序列长度为100个样点。 其中n=0…99，f1=1kHz，f2=2kHz，fs=8kHz。 2、采用LMS算法，均衡器输入为训练序列加上干扰，均衡器阶数为21阶，步长因子β=0.01。 3、在Matlab中编写浮点LMS算法，绘制均衡器的输出波形，并与训练序列进行对比。 (1, the system only in the training status. The training sequence is 2cos (2πf1n/fs), interference sin (2πf2n/fs) sequence length of 100 samples. Where n = 0 ... 99, f1 = 1kHz, f2 = 2kHz, fs = 8kHz. 2, using LMS algorithm, the input to the equalizer training sequence plus interference equalizer order is 21 bands, step factor β = 0.01. 3, the preparation of the floating-point LMS algorithm in Matlab, draw the output waveform equalizer, and with the training sequence comparison.)