KALMAN

Creation, transformations, algorithms and visualization of geometrical 3D primitives, such as points, lines, planes, polyhedra, circles and spheres.

channel flow computation

Based on Linear Membership

以优化SVM算法的参数c和g为例，对GWO算法MATLAB源码进行了逐行中文注解。 是很好的学习材料。(SVM algorithm to optimize the parameters c and g, for example, for GWO algorithm MATLAB source was progressive Chinese annotations. It is a good learning materials.)

least square SVM toolbox

实现维纳滤波器的设计，进过实践完全可行，请放心下载(Achieve Wiener filter design, into the practice entirely feasible, please rest assured download)

续上一个程序的控制算法代码，非线性滑模变结构控制方法的程序，调试运行正确。(continuation of a process control algorithm code, nonlinear SMVSC control procedures, debugging and running correctly.)

利用basis pursuit算法计算图形重建，利用compressive sensing技术使用较少的数据进行图形恢复(Use basis pursuit graphic reconstruction algorithm using compressive sensing technology uses less data graphically recovery)

一些自适应信号处理的算法，包括广义互相关函数GCC时延估计，基于kaiser窗的双谱线插值FFT谐波分析。( Some adaptive signal processing algorithms, Including the generalized cross-correlation function GCC time delay estimation, Dual-line interpolation FFT harmonic analysis kaiser windows.)

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