ELM-MATLAB-GPU

利用matlab进行电机的直接转矩控制仿真，十分详细(dtc matlab simulink)

该文件包含图像处理的常用的图像处理工具箱，较适合没有MATLAB基础的人员入门学习，该文件包含实例和常用函数的解释(This document contains commonly used image processing Image Processing Toolbox, MATLAB no more suitable for entry-based learning staff, the document contains examples and explanation of commonly used functions)

inverse dynamic of robot.nt to upload source code, you can

Finally, probability analysis, based on the chosen database, is performed and judgment whether the person is recognized is pronounced. Two different modeling techniques can be suggested for purposes of person identification or verification. The approach based on Hidden Markov Speaker Models (HMMs) with the mixtures of Gaussian distribution is text-dependent one. For this technology a speaker is described by a set of HMMs, constructing the set of speech groups spoken by that person. The speech groups may be phonemes or words [7]. The text-independent technology is rested upon Gaussian Mixture Speaker Models. For this technology each speaker is defined by only one model describing all utterances of that person. Identification in the range of both approaches is executed by evaluation of maximum a posteriori probability [7].

此代码通过matlab实现最小二乘回归线性模型参数功能(least square)

Hi this code for Video Denoising using sparse transformation. simply add the video u can see the difference. it working fine. tested.

matlab voi nhan dang tieng Viet

极限学习机极速学习机\ELM 稀疏表示人脸识别稀疏表示\L0范数求解L1范数ELM神经网络AR人脸数据库基于ELM的图像分类与稳健回归算法研究基于ELM与稀疏表示的混合人脸识别算法 AR人脸识别准确率0.95. 文章:Luo, Minxia, and Kai Zhang. A hybrid approach combining extreme learning machine and sparse representation for image classification. Engineering Applications of Artificial Intelligence 27 (2014): 228-235.(Matlab codes of the following paper: Luo, Minxia, and Kai Zhang. A hybrid approach combining extreme learning machine and sparse representation for image classification. Engineering Applications of Artificial Intelligence 27 (2014): 228-235.)

对matlab数学建模进行了系统的介绍。并配有大量的案例一共学习。适用于初学者(Matlab mathematical modeling for the system were introduced. And total Peiyoutailiang case study. For beginners)

自然激励下建筑结构的模态参数识别，首先通过自然激励技术（next）得到结构的自由响应，然后由自回归滑动平均（arma）方法识别模态参数。(natural incentive structures under the modal parameter identification, First through natural incentive Technology (next) to be free to respond to the structure, then autoregressive moving average (arma) identified modal parameters.)