When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    This alternative definition is significantly more widespread: machine epsilon is the difference between 1 and the next larger floating point number.This definition is used in language constants in Ada, C, C++, Fortran, MATLAB, Mathematica, Octave, Pascal, Python and Rust etc., and defined in textbooks like «Numerical Recipes» by Press et al.

  3. Levi-Civita symbol - Wikipedia

    en.wikipedia.org/wiki/Levi-Civita_symbol

    In two dimensions, the Levi-Civita symbol is defined by: = {+ (,) = (,) (,) = (,) = The values can be arranged into a 2 × 2 antisymmetric matrix: = (). Use of the two-dimensional symbol is common in condensed matter, and in certain specialized high-energy topics like supersymmetry [1] and twistor theory, [2] where it appears in the context of 2-spinors.

  4. Normalization (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(machine...

    The following is a Python implementation of BatchNorm for 2D convolutions: import numpy as np def batchnorm_cnn ( x , gamma , beta , epsilon = 1e-9 ): # Calculate the mean and variance for each channel. mean = np . mean ( x , axis = ( 0 , 1 , 2 ), keepdims = True ) var = np . var ( x , axis = ( 0 , 1 , 2 ), keepdims = True ) # Normalize the ...

  5. Epsilon number - Wikipedia

    en.wikipedia.org/wiki/Epsilon_number

    The fixed points of the "epsilon mapping" form a normal function, whose fixed points form a normal function; this is known as the Veblen hierarchy (the Veblen functions with base φ 0 (α) = ω α). In the notation of the Veblen hierarchy, the epsilon mapping is φ 1 , and its fixed points are enumerated by φ 2 (see ordinal collapsing function .)

  6. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]

  7. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    def f (x): return x ** 2-2 # f(x) = x^2 - 2 def f_prime (x): return 2 * x # f'(x) = 2x def newtons_method (x0, f, f_prime, tolerance, epsilon, max_iterations): """Newton's method Args: x0: The initial guess f: The function whose root we are trying to find f_prime: The derivative of the function tolerance: Stop when iterations change by less ...

  8. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.

  9. Talk:Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Talk:Machine_epsilon

    And more generally, you can use the nextafter family of functions from math.h; for example, "nextafter(1.0, 2.0) - 1.0" should evaluate to DBL_EPSILON if I'm not mistaken. (By the way, the C standard even gives an example showing what this constant should be if you use IEEE floating point numbers: DBL_EPSILON = 2.2204460492503131E-16 = 0X1P-52.)