MATLAB7_0

Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.

用Hanning窗设计线性相位滤波器，绘制幅频和相位特性曲线，并在改变N的值后观察N对滤波器特性的影响及其时域特点。(Hanning window with a linear phase filter design, drawing amplitude frequency and phase characteristic curve, and change the value of N, N were observed on the filter characteristics and time domain characteristics.)

飞行器纵向3自由度非线性动力学模型的线性化(Aircraft vertical 3-DOF nonlinear dynamic model linearization)

考虑不平衡磁拉力作用下，转子的轴心轨迹变化求解方法。(unbalanced magnetic pull )

数字识别基于MATLAB的数字识别系统的研究与实现(Digital Identification)

this is the basic ofdm simulation of an ofdm signal

simulare motor de curent continuu

Read video into MATLAB using aviread and alculate the background image . Initialization for Kalman Filtering. Calculate the difference image to extract pixels with more thanthreshold change. and Plot the tracking rectangle after Kalman filtering

汉诺塔的实现程序，包括简单的实现代码，和动画演示代码(Hanoi' s implementation procedures, including simple implementation code, and animation demo code)

BPSK in Simulink. I m only sharing this work with you.