bcmpar

说明：  一种经典的流形学习算法，IsomapR1，用matlab与c++混合编程实现(A classical manifold learning algorithms)

SIFT特征和正交DLT算法在物体识别中的应用.(SIFT features and orthogonal DLT algorithm in object recognition.)

SMULINK model for simulation of communication delay

均匀圆阵MUSIC算法，不同信噪比下对信号俯仰角估计性能，用均方根误差表示；采用谱峰搜索寻找最大值对应坐标；(UCA MUSIC to estimate elevation angle vernus different SNRs，describe with RMSE search the spectral peak and fing the maximum )

说明：  中文版完善的matlab simulink 电气模块设计（SimPowerSystems）使用说明，一步一步教你电气模块(Chinese version of matlab simulink comprehensive modular design Electrical (SimPowerSystems) the use of that teach you step-by-step electrical module)

Discrete Orthogonal Polynomial Toolbox: DOPBox Version 1.5

台湾大学PLL讲义讲稿 讲稿里包括Phase-Locked Loops的工作方式，简化模型，仿真图及其应用。(National Taiwan University PLL lecture Script to include in Phase-Locked Loops work, the simplified model, the simulation diagram and its application )

基于MATLAB牛顿拉夫逊潮流计算的计算机算法(A computer algorithm for power flow calculation based on MATLAB Newton Ralph Xun)

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.

主要用于直线检测，可以检测多条直线，但参数设置不好的话，效果并不是很好(Line detection)