Tsteepest_desh

LDPC编码的C语言实现。包括校验矩阵，生产矩阵的生成，编码，译码等。(LDPC coding in C language. Including the parity matrix, matrix production generation, encoding, decoding and the like.)

LDPC的译码算法，其中使用matlab和C的联合编程，C主要做了译码算法，并且有性能的仿真测试(LDPC decoding algorithm, including joint programming matlab and C, C major to do the decoding algorithm and performance simulation test)

qQq QqQ qQ<WXWXC qQSQSQ

matlab形态学处理的程序之连接两点之间的直线(a program to read a move into matlab for detection)

Matlab interface for the image segmentation algorithm of Efficient Graph-Based Image Segmentation Pedro F. Felzenszwalb and Daniel P. Huttenlocher International Journal of Computer Vision, 59(2) September 2004.

- XCS for Dynamic Environments + Continuous versions of XCS + Test problem: real multiplexer + Experiments: XCS is explored in dynamic environments with different magnitudes of change to the underlying concepts. +Reference papers: H.H. Dam, H.A. Abbass, C.J. Lokan, Evolutionary Online Data Mining – an Investigation in a Dynamic Environment. 2005, accepted for a book chapter in Springer Series on Studies in Computational Intelligence H.H. Dam, H.A. Abbass, C.J. Lokan, Be Real! XCS with Continuous-Valued Inputs. IWLCS 2005, (International Workshop on Learning Classifier Systems). Washington DC, June 2005.(- XCS for Continuous Dynamic Environments Test versions of XCS problem : real multiplexer Experiments : XCS is explored in dynamic environments with di fferent magnitudes of change to the underlying concepts. Reference papers : H. H. Dam, H. A. Abbass, C. J. Lokan. Evolutionary Online Data Mining-an Investiga tion in a Dynamic Environment. 2005. accepted for a book chapter in Springer Series o n Studies in Computational Intelligence H.H. D am, H. A. Abbass, C. J. Lokan. Be Real! XCS with Continuous- Valued Inputs. IW LCS 2005. (International Workshop on Learning Classifi er Systems). Washington DC, June 2005.)

matlab数值计算，入门基础，绝对好用(matlab numerical calculation, entry-foundation, absolutely easy to use)

用k2算法从先验概率构建贝叶斯网络，实现推理，结构学习，参数学习用贝叶斯方法。(K2 algorithm using Bayesian network built from the a priori probability to achieve reasoning, structure learning, parameter learning.)

利用幂法和反幂法求解按模最小特征值，按模最大特征值。与MATLAB中eig功能相似 (get the character value of a matrix, similiar with the function eig in matlab)

可以简单的实现快速傅里叶变换，这只是部分的，等开通了账号再把其他的上传上来(Can simply fast Fourier transform)