Cal_Burnup

This function uses SRP-PHAT with Stochastic Region Contraction (SRC) global-optimization algorithm to locate a single source using a frame of data and M microphones.

matlab数理统计工具箱介绍，内含大量数理统计函数的说明(matlab toolbox of mathematical statistics introduction, containing a large number of mathematical description of statistical functions)

UWB，超宽带信号分析必用的子函数，第16部分！(UWB, ultra-wideband signal analysis will be used for Functions, Part 16!)

MATLAB实例详解，通过对matlab语言如何编程进行实例解析，是学习matlab的很好教程(Detailed MATLAB examples, through the matlab programming language for examples of how to resolve, are studying a very good tutorial matlab)

大失准角初始对准。应用UKF进行初始对准； 用于惯性导航初始对准(alignment navigation inertial)

MUSIC算法，信号源相关，信号源相关的，两个信号源(MUSIC,)

PLS - DN是一个有限的牛顿为解决非退化的分段线性系统的算法。 PLS - DN的展品可证明半迭代 财产即在全球范围内的精确解在有限数量的迭代算法收敛。被证明是收敛速度 至少前终止线性。 广泛的算法是在我们的AISTATS 2011纸描述：“一个非退化的分段线性系统的有限牛顿算法”。此演示包重新运行 在解决非负最小二乘法（NNLS）问题上的三个稀疏的设计矩阵，从哈威尔波音收集（达夫等人，1989年）第4.2节的实验。 随着PLS - DN，此演示包建议实施五 其他NNLS求解：LCP_Fisher_Newton，LCP_Lemke，PQN，TRESNEI，和SCD (PLS- DN is a finite non-degenerate Newton to solve the piecewise linear system algorithms. PLS- DN exhibits semi-iterative property to prove that the exact solutions worldwide in a limited number of iterative convergence. Proved to be terminated before the linear convergence rate at least. A wide range of algorithms in our AISTATS 2011 paper describes: " a non-degenerate sub-linear systems with limited Newton algorithm." This demo package to re-run in the settlement of non-negative least squares (NNLS) on the design of the three sparse matrices from the Harwell Boeing collection (Duff et al, 1989) Section 4.2 of the experiment. With PLS- DN, this demonstrates the implementation of five other NNLS package proposed solution: LCP_Fisher_Newton, LCP_Lemke, PQN, TRESNEI, and SCD)

sobel算子进行边缘监测，附有源代码和效果图(sobel operator edge monitoring, with the source code and effect diagram)

产生模拟信号的程序，是我自己写的，毕业设计的时候用到的(Procedures generate analog signals that I wrote it myself, when used in graduate design)

这是一个实现Levenberg-Marquardt算法的MATlAB代码，总共4个文件f.m产生目标评价函数，l_m_trust.m是进行L_M算法迭代处理，trtestlm.m是采用置信域方法决定更新参数和置信系数，而测试函数入口时test_lm.m，每个函数里面有详细的中文注释，希望能给你的工作带来帮助！(This is an implementation of Levenberg-Marquardt algorithm MATlAB code, generated a total of four documents fm objective evaluation function, l_m_trust.m is iterative processing algorithm for L_M, trtestlm.m Confidence region method is used decided to update the parameters and confidence coefficient and the test function entrance test_lm.m)