MATLABfilescmpleteset

code for gauss jordan

Variational inference for Bayesian variable selection

This paper presents an overview of our most recent results concerning the Particle Swarm Optimization (PSO) method. Techniques for the alleviation of local minima, and for detecting multiple minimizers are described. Moreover, results on the ability of the PSO in tackling Multiobjective, Minimax, Integer Programming and
1 errors-in-variables problems, as well as problems in noisy and continuously changing environments, are reported. Finally, a Composite PSO, in which the heuristic parameters of PSO are controlled by a Differential Evolution algorithm during the optimization, is described, and results for many well-known and widely used test functions are given.

雷达信号处理基石,Fundamentals of Radar Signal Processing,source code for this book, including GUI(Fundamentals of Radar Signal Processing,source code for this book, including GUI)

solving the heat equation

通过DLA算法计算产生分形，可通过控制黏贴概率来控制分形维度(Generated through the DLA fractal algorithm, the probability of adhesive can be controlled to control the fractal dimension)

一本经典的数字图像处理的书，使用的是MATLAB的环境，作者是冈萨雷斯(A classic book of digital image processing, using the MATLAB environment, the author is gonzalez )

In this work, we are interested in the problem of the coding channel with impulsive noise, whose goal is to correct the errors due to the channel at the time of a numeric transmission. In particular, the convolutional turbocodes constitutes the last progress in this domain and it is very close to the theoretical limit predicted by Shannon in 1948. The objective of this work is to study and to test this coding with the modulation BPSK, to improve the bit error rate (BER) in presence a additive white impulsive GGD noise using the MAP algorithm.

a radix-2,3 and 5 FFT, hopefully this is new and helpful :)

LADT ECG Compression Algorithm 2