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求解最优化问题里的半定规划问题（SDP）经典并且十分有效的MATLAB程序包(a very efficient package for solving semi-definite programming)

AR自回归模型，主要介绍时间序列分析中重要的一个模型。(AR autoregression model, time series analysis introduces an important model.)

10channel的polyphase滤波器，希望给大家提供一些思路(10channel the polyphase filter, I hope to provide some ideas)

take a input vector which is no of users of b[kx1] and code vector which will be a matrix now s=[Nxk],where then give to matched filter,non-correlating detector, by randomised sequence.

Slow feature analysis using matlab

本文基于BP神经网络应用于预测的原理，提出预测步骤及预测可行性，探讨建立基于BP神经网络的预测模型的关键技术，包括样本的选取与预处理、输入输出变量的选取、隐层节点数的确定、初始权值和阈值的选取、激活函数、训练算法与参数的选取，最后建立合理的网络模型；结合住宅市场的实际情况，建立两类BP 神经网络预测模型：基于时间序列的趋势预测模型以及基于影响因素的回归预测模型，即分别采用神经网络趋势预测和回归预测的思路，把住宅市场的供给、需求与房价的历年数据以及其影响因素的数据分别作为学习样本，建立预测模型，进行预测。(Real estate development risk prediction )

根据不同的地理位置转化坐标的matlab源程序，给出注释，方便修改。(Depending on the geographic coordinate transformation matlab source, give comments, easy to modify.)

Analiza numerica. Teorie si exemple de exercitii rezolvate in mathcad si scilab.

Introduction Icasso is based on running FastICA several times (resampling). Icasso pools all the estimates together and forms clusters bottom-up among them. The basic idea is that a tight cluster of estimates is considered to be a candidate for including a "good" estimate. A centroid of such cluster is considered a more reliable estimates than any estimate from an arbitrary run. (Instead of an average as a centroid, Icasso visualizes and returns a centrotype from each cluster. This is the one of the original estimates that is most similar to other estimates in the same cluster. You can compute the average by using Icasso functions.)

it s low density parity check coding file