Introduction_to_Matlab_Tutorial_1

维纳噪声抑制，1、 实验原理是利用信号之间的相关性进行信号估计，从而将噪声滤除； 2、 辅助观测信号的噪声抑制可利用Wiener-Hopf方程 求出维纳滤波器的系数 ，式中 是 的自相关阵， 是输入信号 和滤波器输入 之间的互相关矢量； (Wiener noise suppression, 1, experiment is the use of the correlation between the signals for signal estimation, which will filter out the noise 2, the auxiliary noise suppression observed signal Wiener-Hopf equation can be obtained by Wiener filter coefficients, where is the autocorrelation matrix, is the input signal and filters the cross-correlation between the input vector )

md5 calcul for generating hashes in 128 bits.Please tell if you like it

这是基于小波的微弱信号检测，小波变化自被提出以来就到得到了广泛的应用，在此就是几个案例(This is a wavelet-based weak signal detection, wavelet changed since it was proposed to have been widely used in several cases this is)

IGBT的boost电路，最简单的，适合初学者(IGBT in the boost circuit, the most simple, suitable for beginners)

解方程，可为相关学习者或者matlab独立编程人员提供参考(Solution of equation for the relevant independent learners or matlab programmers reference)

说明：  硕士论文，主要讲解应用QAM系统的盲均衡自适应算法的仿真及FPGA实现。(Master s thesis about blind Equalization for QAM systems)

这些录音由Thorsten Zander，柏林，和蔼可亲地提供；如果你使用这些录音的出版物，请引用： 赞德，T. O.，Kothe，C.，Jatzev，S.＆Gettne，M（2010）。增强人机交互与主动和被动脑机接口的输入。在大脑-计算机接口中（181-199页）。斯普林格伦敦。(These recordings were kindly provided by Thorsten Zander, TU Berlin; if you use these recordings for a publication, please cite: Zander, T. O., Kothe, C., Jatzev, S., & Gaertner, M. (2010). Enhancing human-computer interaction with input from active and passive brain-computer interfaces. In Brain-Computer Interfaces (pp. 181-199). Springer London.)

采样系统实时信号的频谱分析MATLAB程序(Real-time signal sampling spectral analysis program MATLAB)

information theory fibonnachi

This is a simulation of BPSK modulation and its perfomane