cyliccodes_ranjith

非常实用的web开发帮助资料，本人精心收集的，很好很全面！(Very useful information to help web developers, I carefully collected, very good very comprehensive!)

Voice recognition LPC VS MFCC with K-NN

Sequential Importance Sampling for linear gaussian model.

说明：  awgn的各种实现函数，以及每个函数实现的各种功能(awgn)

matlab计算振子天线增益和极化方向。(matlab for antenna)

matlab中gui界面编程，两个不同的gui之间相互传递数据。(programming in matlab gui interface, between two different gui transfer data.)

创建一个n维的稀疏数组对象，n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而，它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说，稀疏的数据，首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上，如果目标数组的尺寸mxnxp……yxz，然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸（M×N×P×……×Y）XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测，你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )

The basic difference from the variants described above lies on the formation of the second component of the PSO algorithm (related with the personal best solution)

Stock data extractor in matlab

C语言与MATLAB接口,将MATLAB写的仿真程序很方便地引入到自己的C语言应用程序之中.(MATLAB and C language interface MATLAB simulation program written in a very convenient way to introduce themselves to the C language application procedures.)