maineimun

Voice filter speech processing voice filter implementation developement

a matlab code about estimating model order with AIC criteria in modeling

应用于数据处理，针对离散数据进行多元线性回归。(Used in data processing, multiple linear regression for discrete data.)

lagrage polynomial calculation for numaric computation.

系统辨识与自适应控制---MIMO系统递推最小二乘参数估计（本程序针对2入2出系统）(System identification and adaptive control systems--- MIMO recursive least squares parameter estimation (the program for 2 into 2 systems))

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. )

matlab code on super resolution

PPT for an IEEE paper "non-local means with dimensionality reduction and sure-based parameter selection"

周期图法实现白噪声背景下的正弦函数功率谱估计,其中的傅里叶变换和谱估计的步骤都是直接写出,没有调用函数(Periodogram method the sine function in the white noise power spectrum estimation, one of the Fourier transform and spectral estimation steps are to write, not call the function)

车牌图像的初步预处理，实现彩色图像灰度化，输出背景图像，输出黑白图像(Initial license plate image preprocessing, color image graying, output background image, bitonal image)