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fuzzy mean for clustering in the matlab.cluster do in environment 3-dimontional.

wavelab预编译文件，能加速wavelab的运行，给那些matlab不能编译m文件的用户准备的。(wavelab pre-compiled documents can be accelerated wavelab of operation, Matlab not to those documents compiled m users of.)

：为了提升自动控制原理课程的教学质量，改善解决课程中计算复杂、公式繁杂、难以理解等问题，我们将Matlab 仿 真技术运用于这门课程中，这款软件有助于提高学生的主动性和兴趣，促进学生分析理解问题和解决问题的能力。文章 主要介绍了Matlab 的概述和特点，Matlab 仿真技术在自动控制原理课程教学中的应用和实例等内容。(: In order to improve the quality of teaching automatic control theory courses, courses to improve the computational complexity of solving the formula complicated, difficult to understand and so on, we will Matlab simulation technology used in this course, this software helps improve students' initiative and interest, promote students' ability to analyze and understand the problem and solve the problem. The article describes an overview of the content and features of Matlab, Matlab simulation technology in teaching automatic control theory and examples of applications and so on.)

该程序是基于MATLAB的磁悬浮控制系统的离散控制算法实现程序(The program is based on discrete control algorithm based on MATLAB magnetic levitation control system to achieve program)

Test Pointed Signals

Visual c++Matlab图像处理与实用案例精选:图像镜像(Visual c Matlab Image Processing and practical case Featured : Mirror Image)

Abstract There are a number of interesting variable selection methods available beside the regular forward selection and stepwise selection methods. Such approaches include LASSO (Least Absolute Shrinkage and Selection Operator), least angle regression (LARS) and elastic net (LARS-EN) regression. There also exists a method for calculating principal components with sparse loadings. This software package contains Matlab implementations of these functions. The standard implementations of these functions are available as add-on packages in S-Plus and R. Keywords LASSO, LARS, SPCA, Matlab, Elastic Net, Sparse, Sparsity, Variable selection

matlab code for machine learn duda

Photos with people (e.g., family, friends, celebrities, etc.) are the major interest of users. Thus, with the exponentially growing photos, large-scale content-based face image retrieval is an enabling technology for many emerging applications. In this work, we aim to utilize automatically detected human attributes that contain semantic cues of the face photos to improve contentbased face retrieval by constructing semantic codewords for efficient large-scale face retrieval. By leveraging human attributes in a scalable and systematic framework, we propose two orthogonal methods named attribute-enhanced sparse coding and attributeembedded inverted indexing to improve the face retrieval in the offline and online stages. We investigate the effectiveness of different attributes and vital factors essential for face retrieval. Experimenting on two public datasets, the results show that theproposed methods can achieve up to 43.5 relative improvement in MAP compared to the existing methods.

系统辨识与自适应控制程序 ，一个很小的.m文件(System identification and adaptive control procedure, a small. M file)