SegDRM_final

理解随机信号功率谱分析原理和方法。 (1) 生成信号，被淹没在在噪声中； (2) 试用周期图法估计信号的功率谱； (3) 选用不同窗，使用修正周期图法估计信号的功率谱； (4) 对一段语音信号，使用LD算法估计其功率谱； (5) 详细列出功率谱估计的步骤和原理。 (understanding of random signal power spectrum analysis principles and methods. (1) generate signals being drowned in the noise; (2) The probationary period plan estimates the signal power spectrum; (3), different windows, the use of map amendment cycle method to estimate the power spectrum signal; (4) a voice signal, the use of LD algorithm to estimate the gong spectrum; (5) a detailed breakdown of the power spectrum estimation steps and principle.)

时域离散信号的程序代码。。适合初学者进行学习(Discrete time domain signa)

the project is for controlling the mouse with webcamera with unique rGB colurs

druver and indcution motor simulation in matlab

展示了线性、DFE、MLSE均衡器的信噪比性能，并通过蒙特卡罗模拟信道估计结果确定。(This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks. )

使用matlab工具对输入图像进行校正光照不均匀(Using Matlab tool for the input image to correct the uneven illumination)

由信道信号的复数值解调对应的二进制序列由信道信号的复数值找出对应的二进制序列。方法如下：由信道值， ％％求出该值与星座图中所有点的距离，找出距离最小的点，该点对应的 ％％二进制序列及为该信道对应的解调结果。 (Channel signal by the complex demodulation value corresponding to the binary sequence by the complex channel signals to identify the corresponding binary numerical sequence. As follows: by the channel value, the value obtained with the constellation diagram of all points of distance, find the smallest distance between points, the points of the corresponding binary sequence and the corresponding channel demodulation results.)

iradon function with matlab

matlab code to detect and identify the object feature for analysing and compraing purpose

creation and training of single nejron with logsig activation function