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支持向量机(SVM)是数据挖掘中的一个新方法，能非常成功地处理回归问题(时间序列分析)和模式识别(分类问题、判别分析)等诸多问题，并可推广于预测和综合评价等领域，因此可应用于理科、工科和管理等多种学科。目前国际上支持向量机在理论研究和实际应用两方面都正处于飞速发展阶段。它广泛的应用于统计分类以及回归分析中. 支持向量机属于一般化线性分类器.他们也可以认为是提克洛夫规则化（Tikhonov Regularization）方法的一个特例.这族分类器的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. (Support vector machine, the source code)

说明：  摄像机标定经典标定法—— 张正友平面标定法(Zhang camera calibration plane calibration)

卡尔曼滤波的源代码，里面包括了权向量的计算以及MSE的偏差曲线(Kalman filtering of the source code, which includes the calculation of the weight vector and the MSE deviation curve)

对libsvm产生的model进行转换，从原先matlab的mat格式，转换为c语言的文本格式，然后进行预测预测(Allow phonetic typing Libsvm the model converted from the original Matlab mat format, converted to text format c language, and then to predict the forecast)

multi objective differential evolution algorithm

一款很不错的MATLAB优化视频教程，讲述详细，希望用得着的快快分享(A very good video tutorial of MATLAB optimization, described in detail, I hope to share useful for quickly)

说明：  matlab编的标签页，很容很强大~~~~~(matlab code of the tab page, it is very strong capacity ~~~~~)

本人平时收集的惯性导航算法的论文，对搞导航算法的人很有帮助。 1.易于实现的捷联式惯性导航系统仿真.pdf 2.测量运动物体姿态的三自由度定位算法的研究.pdf 3.基于MEMS 技术的微型惯性测量组合.pdf 4.基于四元数的空间全方位算法研究.pdf 5.捷联惯导积分算法设计（连载二）下篇：速度和位置算.pdf 6.数字磁罗经系统的设计.pdf 7.四阶龙格—库塔法在捷联惯导系统姿态解算中的应用.pdf(I normally collected papers inertial navigation algorithm, the navigation algorithm to engage people very helpful. 1. Easy to realize the strapdown inertial navigation system simulation. Pdf2. Measuring movement of three degrees of freedom objects posture positioning algorithm. Pdf3. Based on MEMS technology, micro-inertial measurement unit. Pdf4. Quaternion-based full-space algorithm study. pdf5. SINS Integral Algorithm Design (Part II) next: the speed and position calculation. pdf6. digital magnetic compass system design. pdf7. Fourth-Order Runge- Kutta method in SINS Attitude operator application. pdf)

MATLAB 简单程序，源代码。。。 实现图像变换(Simple MATLAB program, the source code. . . Implementation of Image Transform)

The channel modeling work package WP1 of IST-WINNER project provided a Matlab implementation of the WINNER Phase II Model (referred as WIM this onward). The main purpose of the WIM channel models is to generate a radio channel realisations for a link and system level simulations. The implementation is based on the earlier implementations of WINNER II interim model [6], WINNER I (interim) model [3], 3GPP/3GPP2 Spatial Channel Model (SCM) [4] and SCM(E) Extension models. For details concerning the WIM model, please refer to [1]. This document describes the SW implementation structure of WIM, its input/output interface and its functionality. Channel model scenarios and parameters are modified to correspond to IMT.EVAL [7] channel model.