SVM_plugin_Source_Code.zip - 一个很好的SVM程序，附带安装程序，用于预测和回归分析！,2011-06-04 23:50:34,下载6次
svm_matlab_gui.rar - 支持向量机matlab工具箱（含资料及gui模式）用于分类和回归预测,2011-06-04 23:47:15,下载55次
stprtool.rar - Statistical Pattern Recognition Toolbox for Matlab，Technical University Prague,2011-06-04 23:42:24,下载19次
Variable_KD_Tree_Algorithms_for_Spatial_Pattern_Se - 一篇介绍并行kd tree寻优和参数选取的文章，值得一看！,2010-03-30 20:37:51,下载2次
Nearest_neighbours_and_kD_trees.rar - 利用kd树寻找多维空间最近点的英文书籍，有利于学习ICP算法！,2010-03-30 20:36:22,下载13次
An_intoductory_tutorial_on_kd_trees.rar - 一篇介绍kd-tree算法的比较实用的英文文章，内容详细，有利于初学者使用！,2010-03-30 20:34:49,下载9次
Accelerating_Exact_k_means_Algorithms_with_Geometr - 一篇介绍加速kd树算法的英文文章，有比较高的参考价值！,2010-03-30 20:33:33,下载6次
A_tutorial_on_kd_trees.rar - 一篇介绍k-d tree的入门文章，对图像对准方面的研究人员是很好的参考！,2010-03-30 20:32:05,下载43次
Particle_swarm_optimization.rar - 一篇介绍Particle swarm optimization算法的好文章，适合初学的人！,2010-03-30 20:29:35,下载3次
Particle_swarm_optimization_developments_applicati - 一篇介绍集群优化算法的比较好的文章，适合初次学习的人！,2010-03-30 20:27:55,下载5次
pso_c.rar - 粒子群算法求解常有算法，比较好的资料，c++编写！,2010-03-30 20:06:50,下载4次
swaf_swarm_algorithm_framework_for_numerical_optim - 一片介绍集群智能软件开发的文章，值得一看！,2010-03-30 20:03:47,下载18次
PSOtoolbox.zip - 利用matlab编写的POS集群优化算法的工具箱，值得一看！,2010-03-30 19:59:40,下载8次
GTIFFSample.zip - 可与处理2D和3DTIFF格式图像的控件,2009-11-03 18:10:52,下载9次
NTGraph3D.zip - 一个绘制3D的ActiveX，直接加入工程就能绘制3D图像,2009-11-03 18:08:52,下载31次
MCMC_Unscented_Particle_Filter_demo.rar - 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 Doucet, Nando de Freitas and Eric Wan. The Unscented Particle Filter. Technical report CUED/F-INFENG/TR 380, Cambridge University Department of Engineering, May 2000. After downloading the file, type "tar -xf upf_demos.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab5 and type "demo_MC" for the demo.
,2008-03-07 23:27:02,下载126次
Reversible_Jump_MCMC_Bayesian_Model_Selection.rar - 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 parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
,2008-03-07 23:23:12,下载128次
On-Line_MCMC_Bayesian_Model_Selection.rar - 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 as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.,2008-03-07 23:19:36,下载72次
EMfor_neural_networks.rar - 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 Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
,2008-03-05 19:22:23,下载61次
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 Particle Filtering for Dynamic Bayesian Networks. This detailed discussion of the ABC network should complement the UAI2000 paper by Arnaud Doucet, Nando de Freitas, Kevin Murphy and Stuart Russell. After downloading the file, type "tar -xf demorbpfdbn.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab5 and type "dbnrbpf" for the demo.
,2008-03-05 19:14:12,下载40次
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 software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application. For details, please refer to Rao-Blackwellised Particle Filtering for Fault Diagnosis and On Sequential Simulation-Based Methods for Bayesian Filtering After downloading the file, type "tar -xf demo_rbpf_gauss.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab and run the demo.
,2008-03-05 17:53:59,下载75次