Fraqtive is a program for drawing Mandelbrot and Julia fractals. It uses a very fast algorithm and generates high quality, smooth images.
標簽： Mandelbrot and algorithm Fraqtive
上傳時間： 2016-04-12
上傳用戶：獨孤求源
Burrows Wheeler Transform, Data Compression Algorithm, PDF
標簽： Compression Algorithm Transform Burrows
上傳時間： 2013-12-17
上傳用戶：qlpqlq
Waterfilling algorithm (from [Palomar and Fonollosa, Trans-SP2004]) to compute: pi = (mu*ai - bi)^+ sum(pi) = Pt By Daniel Perez Palomar (last revision: May 10, 2004).
標簽： Waterfilling Fonollosa algorithm Trans-SP
上傳時間： 2014-01-10
上傳用戶：liansi
Pixel Labeled Algorithm Based on Recursive M ethod of Connecting Area in Binary Images
標簽： Connecting Algorithm Recursive Labeled
上傳時間： 2013-12-08
上傳用戶：refent
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.
標簽： Rauch-Tung-Striebel algorithm smoother which
上傳時間： 2016-04-15
上傳用戶：zhenyushaw
Real Value FFT Algorithm
上傳時間： 2014-01-21
上傳用戶：Divine
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.
標簽： sequential reversible algorithm nstrates
上傳時間： 2014-01-18
上傳用戶：康郎
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.
標簽： reversible algorithm the nstrates
上傳時間： 2014-01-08
上傳用戶：cuibaigao
lz77算法("A Universal Algorithm for Sequential Data Compression")的一種簡潔直觀的實現(xiàn)。
標簽： Compression Sequential Universal Algorithm
上傳時間： 2014-11-18
上傳用戶：362279997
genetic algorithm with java
標簽： algorithm genetic with java
上傳時間： 2013-12-19
上傳用戶：lepoke
