Zero_forcingBER

hough 变换实现直线检测 在噪声服从高斯分布的背景中构造信噪比为2、长度为34像素的目标线段；在找出线段所在直线后，在采用固定长线段滑动的方法，确定线段的起始点，最终确定线段的确切位置。(hough transform line detection in the noise to obey Gaussian distribution of the background-noise ratio for the structure 2, with a length of 34 pixels of the target segment at to find out where the straight line segment after the introduction of fixed long-term method of sliding paragraph to determine the segment of starting point, and ultimately determine the exact location of line segments.)

DSL上行传输过程中，用户减少后重新估计信道的算法。(DSL upstream, the user re-estimate the channel reduction algorithm)

Matlab Code for simulation of a MIMO systems

matlab NAkagami硕士论文一篇(matlab simulnik NAkagami bachelor paper)

标准粒子群算法求解非线性方程，用MATLAB实现，并出仿真结果(The standard particle swarm algorithm for solving nonlinear equations, using MATLAB to achieve, and the simulation results)

说明：  讲述了高阶谱在信号估计中的应用，并使用matlab来进行演示，讲解。(Described the high spectral signal estimation, and use matlab to demonstrate, explain.)

实现一个单相不控的全桥整流器 交流母线电阻R1，直流滤波电容C，负载电阻R(achieve a single-phase control is not a full-bridge rectifier AC Bus resistor R1, DC filtering capacitor C, load resistor R)

提供了一种图像相位恢复算法，此算法为gs算法，本代码为gs算法最基础的代码。(An image phase recovery algorithm is provided. This algorithm is the GS algorithm. This code is the most basic code of the GS algorithm.)

Speech Recognition - Numbers 1 to 5 Energy normalization and time alignment References: [1] L. Rabiner and B.H. Juang,Fundamentals of Speech Recognition, Prentice-Hall, 1993. ％ [2] P.E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, 1987. ％ [3] J.D. Markel and A.H. Gray,Linear Prediction of Speech(Speech Recognition-Numbers 1 to 5 Energy n ormalization and time alignment References : [1] L. Paras and B. H. Juang, Fundamentals of Speech Recognition. Prentice-Hall, 1993. % [2] P. E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, 1987. % [3] J. D. Markel and A. H. Gray, Linear Prediction of Speech)

采用matlab，实现了gabor滤波的核心功能(gabor filter is very famous and really useful for texture feature extraction and image retrivel. attached code is wrriten well using matlab. More detail can be referenced in the paper <texture features for browsing and retrieval of image data>)