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脑功能近红外光谱成像中的运动伪迹移除方法基于卡尔曼滤波和wiener滤波(Motion artifact removal methods based on Kalman filtering and wiener filtering in brain functional near-infrared spectroscopic imaging)

稀疏表示字典的训练方法，由压缩感知领域大神M. Elad公布的matlab工具包(matlab tools for K-SVD)

说明：  包含蚁群，模拟退火，遗传等算法解决TSP问题的matlab代码。(Include ant colonies, simulated annealing and genetic algorithm to solve TSP problem matlab code.)

Ham for dnoosing excelent resuls will be obtained from this

matlab程序，用于雷达mti处理算法仿真分析(radar mti processing simulation)

工具箱主要功能: 1） 姿态向量、四元数、矩阵、滤波算法等各类子程序 2） 圆锥运动仿真 划船运动仿真 惯性器件随机误差仿真 3） Kalman滤波初始对准 基于惯性系初始对准 罗经法初始对准 大方位失准角EKF初始对准 大失准角UKF初始对准 速度+姿态传递对准 4） 纯惯性导航SINS仿真 航位推算、SINS/DR仿真 SINS/GPS组合仿真 GPS/BD/GLONASS单点伪距定位 SINS/GPS松/紧组合 POS正逆向数据处理与信息融合仿真 5）(Toolbox main functions: 1) attitude vector, quaternion, matrix, filtering algorithms and other subroutines 2) conical motion simulation rowing simulation inertial device random error simulation 3) Kalman filtering based on initial alignment of inertial gyrocompass initial alignment law initial alignment of large azimuth misalignment angle EKF initial Alignment of large misalignment UKF initial alignment speed+ attitude transfer Alignment 4) pure SINS simulation inertial navigation dead reckoning, SINS/DR simulation SINS/GPS Integrated simulation of GPS/BD/GLONASS pseudoranges single point positioning SINS/GPS loose/tight combination of forward and reverse POS data processing and information fusion simulation 5))

很细详细、全面的介绍了MATLAB，含有编程实例(This paper introduces MATLAB in detail and comprehensively, including programming examples.)

各种格式图像间的转换，图像的基本操作常用函数(Transition between images in various formats, the basic operation of common functions image)

This document covers various aspects the Heston model. The structure and topics covered is as follows: Chapter 1 introduces the model and provides theoretical and graphical motivation for its robustness and hence popularity. It also discusses pricing using the Partial Differential Equation and Equivalent Martingale Measure techniques Chapter 2 discusses how the different components of the model can be evaluated computationally and how this can be achieved with different methods. These methods are then compared to each other. Chapter 3 addresses the calibration problem. Different methods are presented as well as practical implementation, results thereof, and comparisons. All the MATLAB code required to implement the model is provided in the appendix

基于hessian矩阵的图像处理，，内附hessian的matlab源码 (Hessian matrix-based image processingg, matlab source containing the hessian )