ANSYS)

这是一类特殊的椭圆偏微分方程Helmhotz方程。该程序是用迭代法求解Helmhotz方程的。(This is a special class of elliptic partial differential equations Helmhotz. The procedure is iterative method for solving equations Helmhotz.)

蒙特卡罗方法模拟137Cs源的662keVγ射线在NaI(Tl)闪烁体中的输运过程。开发环境:MATLAB(Monte Carlo simulation of 137Cs sources 662keVγ-ray in NaI (Tl) scintillator of the transport process. Development Environment: MATLAB)

基于matlab的源程序，用于绘制Rosslor方程的相图以及庞加莱截面(Based on matlab source program，used to draw phase diagram, poincare section of Rosslor equation )

本书的目的是让读者熟练掌握MATLAB的知识并用来求解工程问题。解决这类问题一般需要编写相对较短、使用次数较少的程序。因此，本书将着重介绍在MATLAB中如何有效地开发简洁易读的程序，同时使之具有易于调试和执行速度快的特点。(The purpose of this book is to allow readers to master knowledge of MATLAB and used to solve engineering problems. To solve such problems usually need to write a relatively short period, the use of fewer procedures. Therefore, this book will focus on how to effectively develop in MATLAB concise, easy-to-read program, so that it has easy debugging and execution speed.)

运用相关分析法来进行系统辨识，采用的是M序列输入信号。(Carried out using correlation analysis, system identification, using the M sequence input signal.)

说明：  羽毛球排的跟踪程序!非常的游泳,自己多看看(Badminton schedule follow-up procedures! Is the swimming, take a look at their multi-)

MATLAB汽车车牌定位程序 有详细的注解 大家可以参考下(MATLAB vehicle license plate location process in more detail we can refer to the notes under the)

Brief Training Document of Matlab

AirPort Conveyer Belt Model files in matlab

虽然奇异值分解（SVD）和特征值分解（EVD的）是行之有效的，可以通过先进的设施设备先进的算法，它不是通常所说，有一个内在的迹象，可以显着影响的不确定性的结论计算及诠释来自其结果。我们提供一个解决方案，标志模糊的问题确定了从奇异向量的内积和个人数据载体签署奇异向量的迹象。该数据可能有不同的载体，但它有它自身的定位和实际意义的选择方向，其中多数的向量点。这可以通过评估发现了内心的签署标志产品的总和。(Although the Singular Value Decomposition (SVD) and eigenvalue decomposition (EVD) are well-established and can be computed via state-of-the-art algorithms, it is not commonly mentioned that there is an intrinsic sign indeterminacy that can significantly impact the conclusions and interpretations drawn from their results. We provide a solution to the sign ambiguity problem by determining the sign of the singular vector from the sign of the inner product of the singular vector and the individual data vectors. The data vectors may have different orientation but it makes intuitive as well as practical sense to choose the direction in which the majority of the vectors point. This can be found by assessing the sign of the sum of the signed inner products. )