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This module provides an interface to an alphanumeric display module. The current version of this driver supports any alphanumeric LCD module based on the:Hitachi HD44780 DOT MATRIX LCD controller.

书系统地介绍MATLAB 7.0的混合编程方法和技巧。全书共分为13章。第1章和第2章介绍MATLAB的基础知识，第3章简要介绍MATLAB混合编程，第4章至第9章分别介绍几种典型的混合编程方法，包括C-MEX、MATLAB引擎、MAT数据文件共享、Mideva、Matrix和Add-in。第10章、第11章介绍MATLAB与Delphi和Excel的混合编程。第12章介绍MATLAB C ...

the text file QMLE contains the quasi maximum likelyhood estimating procedure and performing Information Matrix test for a univariate GARCH(1,1) model

常见java数据结构的使用方法，包括Arrays类Collections类HashSet类List类TreeSet类Map类Vector类

These instances, whenmapped to an N-dimensional space, represent a core set that can be used to construct an approximation to theminimumenclosing ball. Solving the SVMlearning problem on these core sets can produce a good approximation solution in very fast speed. For example, the core-vector machin ...

This toolbox was designed as a teaching aid, which matlab is particularly good for since source code is relatively legible and simple to modify. However, it is still reasonably fast if used with the supplied optimiser. However, if you really want to speed things up you should consider compiling the ...

PRINCIPLE: The UVE algorithm detects and eliminates from a PLS model (including from 1 to A components) those variables that do not carry any relevant information to model Y. The criterion used to trace the un-informative variables is the reliability of the regression coefficients: c_j=mean(b_j)/std ...

The ISD51_Demo project for the MSC1200 shows how to use the ISD51 In-System-Debugger with flash breakpoints or hardware breakpoints. By default, it is configured for flash breakpoints which allow you to set real-time breakpoints in your software. Using Flash breakpoints has also the benefit that no ...

Batch version of the back-propagation algorithm. ％ Given a set of corresponding input-output pairs and an initial network ％ [W1,W2,critvec,iter]=batbp(NetDef,W1,W2,PHI,Y,trparms) trains the ％ network with backpropagation. ％ ％ The activation functions must be either linear or tanh. The network ...

％ Train a two layer neural network with the Levenberg-Marquardt ％ method. ％ ％ If desired, it is possible to use regularization by ％ weight decay. Also pruned (ie. not fully connected) networks can ％ be trained. ％ ％ Given a set of corresponding input-output pairs and an initial ％ network, ％ ...