BEM_Bing_LIU

用lin法求高阶方程，可解特征方程, 可以是两队复根，可以是一对复根和两个实根，也可以是四个实根。(lin method, solve latent function)

matlab经典算法方程中关于解方程问题的具体内容 可以给需要的朋友们一些启示(classical algorithm matlab problem solving equations equations on the specific content of a friend in need who can give some inspiration)

包含试验得到的风速普，Kaimal谱及其曲线，可以在ANSYS里加载。(This source contains several wind speed spectrum,such as Kaimal spectrum.)

The code accompanying Understanding and Implementing the Finite Element Method by Mark S. Gockenbach (SIAM, 2006)(is contained in four directories: 1. version1: linear Lagrange triangles 2. version2: Lagrange triangles of arbitrary degree 3. version3: isoparametric elements of arbitrary degree 4. adaptive: local refinement, a posteriori error estimates, etc.)

A simple minimizer of in-line coded functions, for teaching and experimentation

RSSI 定位算法的MATLAB仿真实现(RSSI positioning algorithm matlab)

现代功率谱估计，信号与信息处理，music算法(Moderne Leistungsspektrum Schä tzung, Signal-und Informationsverarbeitung, Musik-Algorithmus)

calculation of gaussian filter

介绍了如何在matlab中最短路径的实现问题(Describes how the shortest path in matlab implementation issues)

MMT is a Matlab toolbox implementing the multi-task Lasso models, including: (i) the Lasso (ii) the standard multi-task Lasso, i.e. the group Lasso (iii) the structured input-output multi-task Lasso, a.k.a. the two-graph guided multi-task Lasso proposed in [1]. The last case (iii) subsumes the special cases: tree-guided and the feature-graph guided multi-task Lasso. The core optimization algorithm for solving this model is developed in C to enhance greater computational efficiency. In particular, current scalability of the coefficient matrix that has been tested for MMT is 104*104! The structured input-output multi-task Lasso model is well-suited for addressing the expression quantitative trait loci (eQTL) mapping problems which are of the intrinsic high-dimensional nature. Details can be found in [1].