By defining the adjacency matrix to calculate the shortest path between node len...

该报告详细介绍了Viterbi译码的方法，并分析了从卷积编码，调制，信道，解调，译码的详细步骤。(this article introduce the decoding way of convolutional code，and analysis the steps from coding ，modulating，channel，demodulating，and decoding。)

说明：  用于文本分析的pLSA(Probability Latent Semantic Analysis)的Matlab算法，含有测试数据及算法原理介绍。也可用于图像分析。(IpLSA (Probability Latent Semantic Analysis) Matlab惴ㄐ?菁惴ㄔ?堋 也 图)

雷达系统分析与设计（matlab），非常清晰的pdf(Radar Systems Analysis and Design Using MatLab)

matlab常用函数查询，编程很有用的东西。(matlab commonly used functions query)

With FR conjugate gradient method for solving unconstrained problem

MIMO系统的几种信道估计仿真，很有用，已经运行(MIMO system, several channel estimation algorithm simulation, useful, and has been runned)

its a c program for assembler

matlab环境下高斯信道中采用BPSK调制的误码率仿真。(Matlab environment Gaussian channel BPSK modulation BER simulation)

 这是一个关于稀疏高斯过程的matlab源码，可以用于计算测试输入的高斯预测值 "spgp_pred" computes the SPGP predictive distribution for a set of test inputs. You need to supply a set of "pseudo-inputs" or "basis vectors" for the approximation, and suitable hyperparameters for the covariance. You can use any method you like for finding the "pseudo-inputs", with the simplest obviously being a random subset of the data. It is coded for Gaussian covariance function, but you could very easily alter this. It is also fine to use for high dimensional data sets. "spgp_lik" is the SPGP (negative) marginal likelihood and gradients with respect to pseudo-inputs and hyperparameters. So you can use this if you wish to try to optimize the positioning of pseudo-inputs and find good hyperparameters, before using "spgp_pred". I would recommend initializing the pseudo-inputs on a random subset of the data, and initializing

跟踪目标的算法，camshift,meanshift.(Target tracking algorithm, camshift, meanshift.)