liusiqam

学校关于自动化课程MATLAB的课程设计要求(The school curriculum on the automation design requirements of the course MATLAB)

75 份速查表，由 vikas 收集整理，包括：jQuery、HTML、HTML5、CSS、CSS3、JavaScript、Photoshop 、git、Linux、Java、Perl、PHP、Python、Ruby、Ruby on Rails、Scala、C#、SQLite、C++、C语言、Ubuntu、WordPress、Node.js、Oracle、NMAP、Mac OS X、Haskell、Unicode、PostgreSQL、Lisp、Matlab 等。(List of 75 parts by vikas collected, including: jQuery, HTML, HTML5, CSS, CSS3, JavaScript, Photoshop, git, Linux, Java, Perl, PHP, Python, Ruby, Ruby on Rails, Scala, C#, SQLite , C++, C language, Ubuntu, WordPress, Node.js, Oracle, NMAP, Mac OS X, Haskell, Unicode, PostgreSQL, Lisp, Matlab etc.)

BUCK电路，具有先恒流在恒压的功能，采用双环控制(BUCK circuit, with the first constant current constant pressure, double-loop control)

基于LMS算法的回声消除仿真(LMS algorithm based on the echo canceller Simulation)

Bit error rate performance of BPSK over Rayleigh fading wireless channel and its comparison with ber of BPSK transmission over AWGN channel.

用matlab做的最小二乘法外推多项式拟合卫星周跳，可以学习。(Using matlab to do the least squares polynomial fitting extrapolation satellite cycle slips, you can learn.)

edge detection using fuzzy and canny operator

WSNs的LEACH路由算法，它是一种层次型算法，核心思想是分簇，并轮流当选簇头！(WSNs LEACH routing algorithm, which is a hierarchical algorithm, the core idea is clustering, and turns elected cluster head!)

MUSIC算法是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成 (MUSIC algorithm is a feature space based on matrix decomposition method. From the geometric point of view, the observed signal space can be decomposed into signal subspace and noise subspace, it is clear that two spaces are orthogonal. Signal subspace to the data received by the array covariance matrix and the eigenvector corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector corresponding to the composition )

说明：  分布式环境的计算，课件的使用，以及各种资源。。。(The research paper of “Segmentation methods of fruit image based on color difference” is mainly about four segmentation methods in fruit-harvesting robot vision, which respectively are dynamic threshold segmentation method, extended Otsu method, improved Otsu combined with genetic arithmetic and adaptive segmentation method based on LVQ network. It is written in a good structure. )