This directory contains 3 file system modules: - file system ISO9660 iso9660.c iso9660.h - file system FAT12/16 fat.c fat.h - file system FAT32 fat32.c fat32.h file.c and file.h contains all high levels functions/macro/definition for your application. fs_variable.c contains all definitions of Variables that can be shared with the all file systems. config.h must contain the definition of the file system used by your application.
标签： 9660 file system directory
上传时间： 2015-03-15
上传用户：脚趾头
自适应(Adaptive)神经网络源程序 The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms.~..~ There are 11 blocks that implement basically these 5 kinds of neural networks: 1) Adaptive Linear Network (ADALINE) 2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm A simulink example regarding the approximation of a scalar nonlinear function of 4 Variables
标签： collection implement Adaptive adaptive
上传时间： 2015-04-09
上传用户：ywqaxiwang
The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms.~..~ There are 11 blocks that implement basically these 5 kinds of neural networks: 1) Adaptive Linear Network (ADALINE) 2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm A simulink example regarding the approximation of a scalar nonlinear function of 4 Variables is included
标签： Neural collection implement Adaptive
上传时间： 2013-12-23
上传用户：teddysha
％ [BestPop,Trace]=fmaxga(FUN,LB,UB,eranum,popsize,pcross,pmutation) ％ Finds a maximum of a function of several Variables. ％ fmaxga solves problems of the form: ％ max F(X) subject to: LB <= X <= UB ％ BestPop--------最优的群体即为最优的染色体群 ％ Trace----------最佳染色体所对应的目标函数值 ％ FUN------------目标函数 ％ LB-------------自变量下限 ％ UB-------------自变量上限 ％ eranum---------种群的代数,取100--1000(默认1000) ％ popsize--------每一代种群的规模；此可取50--100(默认50) ％ pcross---------交叉的概率,此概率一般取0.5--0.85之间较好(默认0.8) ％ pmutation------变异的概率,该概率一般取0.05-0.2左右较好(默认0.1) ％ options--------1×2矩阵,options(1)=0二进制编码(默认0),option(1)~=0十进制编码,option(2)设定求解精度(默认1e-4)
标签： pmutation BestPop popsize maximum
上传时间： 2015-07-16
上传用户：Altman
CCALC provides convenient way to for performing calculations. You can use standard infix notation for expressions and store results in Variables.
标签： calculations convenient performing provides
上传时间： 2015-08-18
上传用户：dave520l
This lab exercise will cover the use of AccelDSP’s design exploration capabilities that include mapping Variables to memory and unrolling loop and vector operations. You will learn how to create different hardware architectures without modifying the MATLAB source to explore different area/performance tradeoffs.
标签： capabilities exploration AccelDSP exercise
上传时间： 2014-12-22
上传用户：eclipse
We propose a novel approach for head tracking, which combines particle filters with Isomap. The particle filter works on the low-dimensional embedding of training images. It indexes into the Isomap with its state Variables to find the closest template for each particle. The most weighted particle approximates the location of head. We develop a synthetic video sequence to test our technique. The results we get show that the tracker tracks the head which changes position, poses and lighting conditions.
标签： approach combines particle tracking
上传时间： 2016-01-02
上传用户：yy541071797
8051 Web Server project See Makefile for build notes Written for Keil C51 V5.1 compiler, notes: It uses big endian order, which is the same as the network byte order, unlike x86 systems. Use OPTIMIZE(2)or higher so that automatic Variables get shared // between functions, to stay within the 256 bytes idata space
标签： notes for Makefile compiler
上传时间： 2013-12-17
上传用户：ikemada
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.
标签： reversible algorithm the nstrates
上传时间： 2014-01-08
上传用户：cuibaigao
4. Write a program that sorts three integers. The integers are entered from the console and stored in Variables num1, num2 and num3, respectively. The program sorts the numbers so that num1 <= num2 <= num3.
标签： integers program entered console
上传时间： 2016-05-05
上传用户：龙飞艇
