gperiodic is a program for browsing the periodic table and looking up data for different elements. It also features a non-graphical interface. gperiodicOrb是一個瀏覽元素周期表和查詢不同元素的數(shù)據(jù)的程序。它有一個非圖形化的界面。
標(biāo)簽： gperiodic for different browsing
上傳時間： 2013-12-25
上傳用戶：亞亞娟娟123
Client/Server版本 DBISAM compiles directly into your application with no external libraries required. Runtime package support is also provided if so desired. It has a very small footprint and does not require any forms support in Delphi 6, C++Builder 6, and Kylix 2 and higher, which helps keep the size of non-UI applications like services or web applications to a minimum.
標(biāo)簽： application libraries compiles directly
上傳時間： 2015-04-04
上傳用戶：sz_hjbf
Polynomial fit functions === === === === RegressionObject.cls contains a class that provides an easy way to add polynomial regression functionality to any application. If you just want linear regression or a very high degree, no matter: this class has good performance and scales seamlessly with the complexity of your problem.
標(biāo)簽： RegressionObject Polynomial functions contains
上傳時間： 2015-04-06
上傳用戶：rocwangdp
自適應(yīng)(Adaptive)神經(jīng)網(wǎng)絡(luò)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(biāo)簽： collection implement Adaptive adaptive
上傳時間： 2015-04-09
上傳用戶：ywqaxiwang
SR-tree is an index structure for high-dimensional nearest neighbor queries，C++ sourcecode. SR-tree outperforms the R*-tree and the SS-tree especially for high-dimensional and non-uniform data which are likely to appear in the actual image / video applications.
標(biāo)簽： high-dimensional structure neighbor SR-tree
上傳時間： 2013-12-10
上傳用戶：zjf3110
prolog 找路例子程序： === === === === === === Part 1-Adding connections Part 2-Simple Path example | ?- path1(a,b,P,T). will produce the response: T = 15 P = [a,b] ? Part 3 - Non-repeating path As an example, the query: ?- path2(a,h,P,T). will succeed and may produce the bindings: P = [a,depot,b,d,e,f,h] T = 155 Part 4 - Generating a path below a cost threshold As an example, the query: ?- path_below_cost(a,[a,b,c,d,e,f,g,h],RS,300). returns: RS = [a,b,depot,c,d,e,g,f,h] ? RS = [a,c,depot,b,d,e,g,f,h] ? no ==================================
標(biāo)簽： Part connections example prolog
上傳時間： 2015-04-24
上傳用戶：ljt101007
matlab NumMFs = 2 MF1= in3mf1 : gbellmf ,[3 2 -3 0] MF2= in3mf2 : gbellmf ,[3 2 3 0] [Input4] Name = in4 Range = [-3 3] NumMFs = 2 MF1= in4mf1 : gbellmf ,[3 2 -3 0] MF2= in4mf2 : gbellmf ,[3 2 3 0] [Output1] Name = out Range = [-10 10] NumMFs = 16 MF1= outmf1 : linear ,[41.3729301501 10.029755738 3.1622770253 4.2875458985
標(biāo)簽： gbellmf matlab NumMFs Input4
上傳時間： 2015-04-28
上傳用戶：努力努力再努力
The subject which is to us propos¨¦ is as follows: calculation of the degr¨¦ d¡ ¯ inconsistance d¡ ¯ un logical program possibilist in C++. We thus work on a logical program possibilist, it be-¨¤-statement a logical program resulting from non-classique logic. The goal first of this project is of d¨¦ terminer if a logical program is consisting or not of share the calculation of sound degr¨¦ d¡ ¯ inconsistance.
標(biāo)簽： brvbar calculation subject follows
上傳時間： 2013-12-18
上傳用戶：yulg
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(biāo)簽： Neural collection implement Adaptive
上傳時間： 2013-12-23
上傳用戶：teddysha
The tar file contains the following files: ptfsf.c: heart of the perfect TFSF code ptfsf.h: header file for same ptfsf-demo.c: FDTD code which demonstrates use of perfect TFSF code. Essentially this program used to generate results shown in the paper ptfsf-file-maker.c: code to generate an incident-field file using the "perfect" incident fields ptfsf-demo-file.c: FDTD code which uses the perfect incident fields stored in a file fdtdgen.h: defines macros used in much of my code Makefile: simple make-file to compile programs Also include are some simple script files to run the programs with reasonable values. The code assumes a two-dimensional computational domain with TMz polarization (i.e., non-zero field Ez, Hx, and Hy). The program is currently written so that the incident field always strikes the lower-left corner of the total-field region first. (If you want a different corner, that should be a fairly simple tweak to the code, but for now you ll have to make that tweak yourself.)
標(biāo)簽： ptfsf following the contains
上傳時間： 2013-11-28
上傳用戶：風(fēng)之驕子
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