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  Directory: Visual C++ Books
  Dev tools: Visual C++
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  Update: 2008-12-28
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  Uploader: fbi56fbi
 Describe: ERF function of the original code, erf (x) = (2/root allocation under No.)* (exp (-z side) of the z integral, integral lower limit is 0, the upper limit is x), error function from the form like normal distribution distribution function Φ (x), is a shape such as the normal distribution probability density function do change the results limit points
File list(time 1993010414~2009020816)(Click to check if it's the file you need, and recomment it at the bottom):
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 Search in more than 1820000 codes/documents:
 [C codes in common use] - Codes for functions which are used frequently in numerical calculation ,such as sine function,cosine function, written in C language
 [erf.rar] - This is a use of C language procedures for calculating the error function. Its main characteristic is that from the definition, has a very good refere
 [4ZLJZprobabilitydensityfunctionapproximation.] - pattern recognition algorithm ZLJZ probability density function approximation

 [introductionofalgorithms.rar] - classic algorithms, the book included almost all the classical algorithm, every one of the people trying to run programming will be of great help
 [RandomNumberGenerators.rar] - Random Number Generators (Random Number Generation), including Gaussian random number generator, uniform random number generator, low-frequency genera
 [HighMaPro_matlab.rar] - The book begins with the introduction of the MATLAB programming language, the basic content, on the basis of the system introduced in all areas of app
 [ErrFun.rar] - According the erf function in matlab program, get the value of ERROR function.
 [C4.rar] - Special function 1.г function, beta function, factorial and binomial coefficient 2. Not entirely г function, error function 3. Incomplete beta functio
 [zouxiang_i.rar] - Subsidence deformation. This procedure can give probability integration model calculation of the level of subsidence deformation mobile.
 [fuzzy_control_to_imitate_function.rar] - Using neural network trained to function approximation: y = 8+ 2* exp (1-x. ^ 2) .* cos (2* pi* x)