kalman

kpib.m contains code for GPIB and serial port communication for a number of scientific instruments, organized so that a single common command syntax can operate them all. For example, the command: r = kpib(INSTRUMENT,GPIB, read ) will return the voltage and current reading from a number of different power supplies. The goal is to be able to write matlab code that can accommodate changing instruments and experimental setups with minimum hassle. If INSTRUMENT and GPIB are defined as constants at the beginning of your code, then they can be changed to accommodate new equipment, and the rest of the code is unchanged. In addition, kpib can test whether an instrument exists at an address and read and write arbitrary strings to instruments for testing.

Computes the minimum distance between two different shape polygons. (Vertex-vertex case)

三种求矩阵特征值的matlab实现：乘幂法、QR算法、yaccbi法求特征值(Eigenvalues of the three Matrix matlab implementation: power method, QR algorithm, yaccbi Eigenvalue Method)

各算法对应的问题如下： 　　PSO 用基本粒子群算法求解无约束优化问题 　　YSPSO 用带压缩因子的粒子群算法求解无约束优化问题 　　LinWPSO 用线性递减权重粒子群优化算法求解无约束优化问题 　　SAPSO 用自适应权重粒子群优化算法求解无约束优化问题 　　RandWPSO 用随机权重粒子群优化算法求解无约束优化问题 　　LnCPSO 用学习因子同步变化的粒子群优化算法求解无约束优化问题 　　AsyLnCPSO 用学习因子异步变化的粒子群优化算法求解无约束优化问题 　　SecPSO 用二阶粒子群优化算法求解无约束优化问题 　　SecVibratPSO 用二阶振荡粒子群优化算法求解无约束优化问题 　　CLSPSO 用混沌粒子群优化算法求解无约束优化问题 　　SelPSO 用基于选择的粒子群优化算法求解无约束优化问 　　BreedPSO 用基于交叉遗传的粒子群优化算法求解无约束优化问 　　SimuAPSO 用基于模拟退火的粒子群优化算法求解无约束优化问题(13 PSO algorithms and coursewares)

This is simple lmi buliding algorithm with lmi control toolbox.

说明：  用Matlab实现中值滤波，均值滤波以及高斯滤波(Using Matlab to achieve median filter, mean filter and Gaussian filter)

将一个512×512的lena.bmp图像进行DCT变换，对得到的DCT系数按8×8块进行分层（分三层），重组填充得到新的系数矩阵，结果发现原图像的能量集中在了新图像的左上角低频部分。(The lena.bmp an image of 512 × 512 is subjected to DCT transform, the DCT coefficients obtained by layering 8 × 8 block (of three), to obtain a new recombinant filling coefficient matrix, the energy of the original image is found concentrated in upper left corner of the low-frequency part of the new image.)

matlab在工程数学方面的应用教学文档，matlab是一款功能强大的软件，可以应用于多种领域，本文档着重介绍matlab在工程数学领域的应用。(matlab engineering applications in mathematics teaching document, matlab is a powerful software that can be used in a variety of areas, this document focuses on matlab projects in the field of mathematics.)

说明：  Estimating the positions of sensor nodes is a fundamental and crucial problem in ad hoc wireless sensor networks (WSNs). In this paper, an accurate node localization method for WSNs is devised based on the weighted least squares technique with the use of time-of-arrival measurements. Computer simulations are included to evaluate the performance of the proposed approach by comparing with the classical multidimensional scaling method and Cram´ er-Rao lower bound.

svm-km支持向量机工具箱，特点是他们能够同时最小化经验误差与最大化几何边缘区.因此支持向量机也被称为最大边缘区分类器.(svm-km SVM Toolbox, is characterized by experience that they can while minimizing errors and maximizing geometric border zone. therefore support vector machine is also known as the maximum marginal zone classification.)