<button id="akqeu"></button> 啥也不說了，請看代碼示例 File : fat_dir.c FS_DIR *FS__fat_opendir(const char *pDirName, FS_DIR *pDir) { FS_size_t len FS_u32 unit FS_u32 dstart ....... FS_u32 dsize FS_i32 i char realname[12] char *filename if (!pDir) { return 0 /* No valid pointer to a FS_DIR Structure */ }
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上傳時間： 2013-12-14
上傳用戶：梧桐
自適應(Adaptive)神經網絡源程序 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
標簽： collection implement Adaptive adaptive
上傳時間： 2015-04-09
上傳用戶：ywqaxiwang
ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping Structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical abstracts (MED dataset), that uses BIC to estimate the number of classes and produces keywords for each class. The icaML algorithm is used.
標簽： ICA extension framework classify
上傳時間： 2013-12-22
上傳用戶：himbly
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
標簽： Neural collection implement Adaptive
上傳時間： 2013-12-23
上傳用戶：teddysha
ABAQUS is a general purpose finite element analysis program which is widely used to analyses mechanical, Structure and civil engineering problems. Abaqus has some special feature for analysing fracture mechanics problems, and therefore it is a main tools for the FE-analysis in the Fracture Group at the Mechanical Engineering at Glasgow Universtity. The software which can transfer data from Abaqus into a Matlab readable environment has been developed as a part of a research program in Constraint Estimation in Fracture Mechanics. This research program was funded by a grant from the Defence Research Agency through Prof. J. Sumpter.
標簽： analysis analyses general element
上傳時間： 2015-05-13
上傳用戶：xfbs821
There are some 79 or so Matlab files here which will help in many aspects of the computer vision Structure from motion problem, a full description is provided in the manual, torrsam.ps.
標簽： computer aspects Matlab vision
上傳時間： 2014-01-02
上傳用戶：xlcky
浙江大學計算機學院數據結構課程的教學課件，就是經典教材《Fundamentals of Data Structure in C》的課件。
上傳時間： 2013-12-31
上傳用戶：fxf126@126.com
基于simulink的uwb仿真 uwb.mdl: UWB model - open this to begin. uwb_lib.mdl: Library blocks for UWB model. uwb_init.m: Initialization called before model is loaded. uwb_settings: Sets up Structure containing system parameters ( uwb in workspace). uwb_imr.m: Initializes UWB channel impulse response. uwb_sv_*.m: Four M-files used to generate channel impulse responses (MAT files).
上傳時間： 2013-12-22
上傳用戶：gengxiaochao
The program was written with some object-orientation in mind, which means that all functions that operate on a certain Structure, has the Structure s name as prefix in the function name, for example "Bitstream_get" which gets bits from a bitstream Structure.
標簽： object-orientation that functions program
上傳時間： 2014-01-15
上傳用戶：epson850
工程計算MATLAB code to calculate the reorthogonalized sine tapers input: N = the length of the time series data to be tapered p = the number of tapers requested I = the gap Structure a vector of length N I(t) = 1 if there is data at time t, t=1, ..., N I(t) = 0 if there is a gap at time t output: X = N-by-p vector of the reorthogonalized sine taper
標簽： the reorthogonalized calculate MATLAB
上傳時間： 2013-12-17
上傳用戶：wangyi39
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