tracker-code-2011.04.26

heapmgrbase program for dynamic memory

该代码基于灰色GM(1,1)算法，使用时，需要在函数中将自变量取为时间序列，可预测任意时间的数值(The code is based on gray GM (1,1) algorithm, when used in the function argument will be taken as time series, can predict the value of any time)

第一步：首先我们需要强大的SNMP信息收集和整理工具，网络中这类工具比较多，如果我们只是监控的话建议使用小巧的monomon即可，当然如果企业内部要自定义建立流量监控站点或服务中心的话可以使用其他支持SNMP的MRTG，PRTG等工具。我们可以到http://monomom.matf.de/download.php地址下载该程序，整个程序只有一个文件(Step one: First of all, we need strong SNMP information to collect and organize tools, network tools such as more, if we only recommend the use of surveillance, then compact monomon can, of course, if the custom-house to set up traffic monitoring site or service center If you can use other support SNMP-MRTG, PRTG, such as instrument. We can http://monomom.matf.de/download.php address to download the program, the whole process only one document)

说明：  救护车的报警程序，分别为1000Hz和800Hz.(Ambulance alarm procedures were 1000Hz and 800Hz.)

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)

MATLABC数学函数库在C语言中的应用(MATLABC math library in C language)

Very Simple Volume Rendering

matlab控制系统设计仿真珍贵案例，附有源代码(matlab control system design and simulation precious case, with source code)

Persian calender hijri 1392 mfile

最新的压缩感知文章，从IEL上精选的，对从事压缩感知的同仁定有很大帮助。(Latest articles compressed sensing, selected from the IEL, compressed sensing colleagues engaged given great help.)