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uml 实例 Digital Sound Recorder: A case study on designing embedded systems using the UML notation.

sharepoint portal server的sdk英文版 The SharePoint Products and Technologies 2003 Software Development Kit (SDK) contains conceptual overviews, programming tasks, samples, and references to guide you in developing solutions based on SharePoint products and technologies.

the handbook of c and c ++, the most important tool for c & c++ user!

fastDNAml is an attempt to solve the same problem as DNAML, but to do so faster and using less memory, so that larger trees and/or more bootstrap replicates become tractable. Much of fastDNAml is merely a recoding of the PHYLIP 3.3 DNAML program from PASCAL to C.

it is used to generate random number to simulate the conmmunication scheme, very useful

This Program Is Designed To Simulate A Spatial Antenna Array System Working On The MUSIC Algorithm For The Angle Of Arrival Estimation And Null Steering Algorithm For The Weights Estimation To The Required Output Radiation Pattern .

This applet illustrates the prediction capabilities of the multi-layer perceptrons. It allows to define an input signal on which prediction will be performed. The user can choose the number of input units, hidden units and output units, as well as the delay between the input series and the predicted ...

The Hopfield model is a distributed model of an associative memory. Neurons are pixels and can take the values of -1 (off) or +1 (on). The network has stored a certain number of pixel patterns. During a retrieval phase, the network is started with some initial configuration and the network dynamics ...

Single-layer neural networks can be trained using various learning algorithms. The best-known algorithms are the Adaline, Perceptron and Backpropagation algorithms for supervised learning. The first two are specific to single-layer neural networks while the third can be generalized to multi-layer pe ...

The EM algorithm is short for Expectation-Maximization algorithm. It is based on an iterative optimization of the centers and widths of the kernels. The aim is to optimize the likelihood that the given data points are generated by a mixture of Gaussians. The numbers next to the Gaussians give the re ...