proficient-MATLAB

梳状导频方式下OFDM系统的LS、LMMSE算法比较(Comb Pilot OFDM system under LS, LMMSE algorithm)

高速磁悬浮永磁同步电机matlab仿真模型(High-speed maglev matlab simulation model of permanent magnet synchronous motors)

说明：  MATLAB实现单摆在外力矩作用下的动画 源程序代码(MATLAB a simple pendulum animation torque under the action of outside source program code)

对模拟的雷达回波信号使用不同小波基对其进行的小波分解。(Radar echo signal simulation using different wavelet bases its wavelet decomposition.)

核数据处理课程设计 能谱谱数据分解方法研究程序，包括了多种滤波平滑方法和寻峰，求峰面积等，非常实用。(Nuclear Data Processing Curriculum design- EDS spectral data decomposition method research program, including a variety of filtering and smoothing methods peak search, find and peak area, very practical.)

灰色预测工具箱。 特性： 0 数据预处理，替换掉一些不符合条件的点：如连续相等的点 1 选择最好的c进行平移变换 2 残差太大的，剔除坏点 3 最后使用 新陈代谢 灰色模型求解（xcdxgm11） 函数： ccfx.m:残差分析 gm11.m:一般的灰色预测工具 xcdxgm11.m:新陈代谢灰色预测工具(Grey toolbox. Features: 1 Data preprocessing, replace the points that do not meet the criteria: If a continuous point equal to 2 to select the best translation transformation c 3 residuals too much, remove dead pixels 4 final model was solved using the metabolism of gray (xcdxgm11) Function: ccfx.m: residual analysis gm11.m: normal gray prediction tools xcdxgm11.m: metabolism gray prediction tools)

对图像进行纹理分析，分几个方向进行的处理。matlab程序(right image texture analysis, in several directions at the moment. Matlab procedures)

non linear Ant colony optimization for continous problem

Simulation of static noise margin of 6T to 10T SRAM cells

Hidden-Unit Conditional Random Fields 工具箱，可以用于训练linearCRF和和L.J.P. van der Maaten, M. Welling 提出的huCRF(We provide Matlab code that implements the training and evaluation of hidden-unit CRFs, as well as code to reproduce the results of our experiments. The code implements four different training algorithms: (1) a batch learner that uses L-BFGS, (2) a stochastic gradient descent learner, (3) an online perceptron training algorithm, and (4) an online large-margin perceptron algorithm. The code can also be used to perform (conditional) herding in hidden-unit CRFs. )