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comp430s.zip
- 和Unix的compress/uncompress兼容的压缩/解压算法16位程序，适合压缩文本或重复字节较多的文件
stcp_stack.tar
- sctp protocol stack please use winZip to uncompress it and run it on Linux platform-sctp protocol stack please use winZip to un compress it and run it on Linux platform
WMVRecompress
- This sample shows the necessary code to recompress a WMV file. It shows reading uncompressed samples, writing uncompressed samples, multi-pass encoding, multi-channel output, and smart recompression. -This samp
demos
- This manual describes how to run the Matlab® Artificial Immune Systems tutorial presentation developed by Leandro de Castro and Fernando Von Zuben. The program files can be downloaded from the following FTP address: f
EMdemo
- n this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional independence structure of a simple DBN. The derivation and details are presented in A Simple Tutorial on Rao-Blackwellised P
rjMCMCsa
- On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dim
RaoBlackwellisedParticleFilteringforDynamicBayesia
- The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The softwar
ParticleFilteringforDynamicConditionallyGaussianMo
- In this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional independence structure of a simple DBN. The derivation and details are presented in A Simple Tutorial on Rao-Blackwellised
EMfor_neural_networks
- In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and W
On-Line_MCMC_Bayesian_Model_Selection
- This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters
Reversible_Jump_MCMC_Bayesian_Model_Selection
- This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model param
MCMC_Unscented_Particle_Filter_demo
- The algorithms are coded in a way that makes it trivial to apply them to other problems. Several generic routines for resampling are provided. The derivation and details are presented in: Rudolph van der Merwe, Arnaud Do
Zlib_Compress_Uncompress
- zLib Compress/uncompress example
UncompressFileGZIP
- Uncompress GZIP file Java example code
UnzipFile
- Uncompress ZIP file Java example code
UncompressFileGZIP
- Uncompress GZIP file Java example code
uncompress
- 压缩解压源代码， 包含压缩和解压的几个源代码-Extracting compressed source code, including compression and decompression of several source code
TestCompress
- 檔案壓縮及解壓縮的演算法 記憶體壓縮及解壓縮的演算法-file compress and uncompress memory compress and uncompress
Uncompress
- 对文件进行加压解压处理，对文件进行加压解压处理-Decompression of files to deal with pressure
Compress-and-uncompress-file
- Compress and uncompress file