face

princip of max matlab nbn

基于Matlab的PID参数最优化设计(fminsearch单纯形法)(Matlab-based design of PID parameter optimization (fminsearch simplex method))

说明：  6RPS工作空间绘制求解matlab程序(6rps workspace solution)

Simple Feature Extraction matlab sorce code, for learning purposes,

LIBSVM使用介绍LIBSVM使用介LIBSVM使用介绍绍LIBSVM使用介绍(LIBSVM use and presentation of LIBSVM use and presentation of the use of IL LIBSVM Shao LIBSVM use and presentation of)

实现有效的学习算法 的稀疏贝叶斯模型，即稀疏贝叶斯matlab工具箱("SparseBayes" is a package of Matlab functions designed to implement an efficient learning algorithm for "Sparse Bayesian" models. The "Version 2" package is an expanded implementation of the algorithm detailed in: Tipping, M. E. and A. C. Faul (2003). "Fast marginal likelihood maximisation for sparse Bayesian models." In C. M. Bishop and B. J. Frey (Eds.), Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, Key West, FL, Jan 3-6. This paper, the accompanying code, and further information regarding Sparse Bayesian models)

用matlab求解的一维黎曼问题的精确解，有限体积格式(Using matlab dimensional Riemannian problem solving an exact solution, finite volume scheme)

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.)

Study of the interaction between wind power plants and SMES systems

说明：  视频水印，在每一帧视频帧上嵌入水印，不可见性良好(video waterMarking,embed the watermark on each frame of video,invisibility is mediocre)