FIR_bandpass

ICML 2008 的一篇文章的源代码：CCA的最小二乘法求解(solve CCA by Least square method)

DBSCAN是一个基于密度的聚类算法。改算法将具有足够高度的区域划分为簇，并可以在带有“噪声”的空间数据库中发现任意形状的聚类。(DBSCAN is a density-based clustering algorithm. Algorithm change will have enough height to the regional cluster. and to be with the "noise" of the spatial database found clusters of arbitrary shape.)

Training Artificial Neural Network. XOR Problem. Summation Units, Log-Sigmoid Neurons with Biases. Input Layer: 2, Hidden Layer: 2, Output Layer: 1 neurons. Returns mean square error between desired and actual outputs. Reference Papers: D. Karaboga, B. Basturk Akay, C. Ozturk, Artificial Bee Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks, LNCS: Modeling Decisions for Artificial Intelligence, 4617/2007, 318-329, 2007. D. Karaboga, C. Ozturk, Neural Networks Training by Artificial Bee Colony Algorithm on Pattern Classification, Neural Network World, 19(3), 279-292, 2009. */

qpsk over rayleigh channel

波达方向DOA估计的程序，其中运用了MUSIC以及两种经典的波束形成的方法（Bartlett以及CAPON)(DOA DOA estimation procedures, as well as the use of two classic MUSIC beamforming method (Bartlett and CAPON))

高教版数值分析的matlab代码,误差与范数,非线性方程（组）的数值解法,解线性方程组的直接方法,解线性方程组的迭代法,矩阵的特征值与特征向量的计算,函数的插值方法,函数逼近与曲线（面）拟合,数值微分，数值积分，常微分方程（组）求解(entire codes for numerical analysis based on matlab)

Estimates the power spectral densities (PSDs) using both the generalized Ridge Regression (GRR) method [Hoerl, Kennard] and the ordinary RR method with loading level decided by the harmonic mean (HKB) and a Bayesian estimator (LW) for deciding the diagonal loading level.

matlab图论着色，内涵可以实现简单的图论着色源代码，实现计算色的多项式等功能(the matlab graph theory coloring)

说明：  混沌时间序列分析及其应用混沌时间序列分析及其应用

This document is intended to serve as an introduction to Wavelet processing through a set of Matlab experiments. These experiments will gives an overview of three fundamental tasks in signal and image processing : signal, denoising and compression. These scripts are selfs contents (needed additional Matlab functions can be downloaded while reading the lectures). Each one of these five lectures should take between 1h and 2h in order to tests the various features of the scripts. One should copy/paste the provided code into a file names e.g. tp1.m, and launch the script directly from Matlab comand line > tp1 . Some of the scripts contains "holes" that you should try to fill on your own. I also provide the complete correction of these lectures as a set of Matlab scripts, but you should try as much as possible to avoid using them. (This document is intended to serve as an introduction to Wavelet processing through a set of Matlab experiments. These experiments will gives an overview of three fundamental tasks in signal and image processing: signal, denoising and compression. These scripts are selfs contents (needed additional Matlab functions can be downloaded while reading the lectures). Each one of these five lectures should take between 1h and 2h in order to tests the various features of the scripts. One should copy/paste the provided code into a file names eg tp1.m, and launch the script directly from Matlab comand line> tp1. Some of the scripts contains holes that you should try to fill on your own.I also provide the complete correction of these lectures as a set of Matlab scripts, but you should try as much as possible to avoid using them.)