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  2. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    A sigmoid function is any mathematical function whose graph has a characteristic S-shaped or sigmoid curve. A common example of a sigmoid function is the logistic function , which is defined by the formula: [ 1 ]

  3. Logistic function - Wikipedia

    en.wikipedia.org/wiki/Logistic_function

    The standard logistic function is the logistic function with parameters =, =, =, which yields = + = + = / / + /.In practice, due to the nature of the exponential function, it is often sufficient to compute the standard logistic function for over a small range of real numbers, such as a range contained in [−6, +6], as it quickly converges very close to its saturation values of 0 and 1.

  4. Generalised logistic function - Wikipedia

    en.wikipedia.org/wiki/Generalised_logistic_function

    The generalized logistic function or curve is an extension of the logistic or sigmoid functions. Originally developed for growth modelling, it allows for more flexible S-shaped curves. The function is sometimes named Richards's curve after F. J. Richards, who proposed the general form for the family of models in 1959.

  5. Gompertz function - Wikipedia

    en.wikipedia.org/wiki/Gompertz_function

    The Gompertz curve or Gompertz function is a type of mathematical model for a time series, named after Benjamin Gompertz (1779–1865). It is a sigmoid function which describes growth as being slowest at the start and end of a given time period.

  6. Smoothstep - Wikipedia

    en.wikipedia.org/wiki/Smoothstep

    The characteristic S-shaped sigmoid curve is obtained with ⁡ only for integers n ≥ 1. The order of the polynomial in the general smoothstep is 2 n + 1. With n = 1, the slopes or first derivatives of the smoothstep are equal to zero at the left and right edge ( x = 0 and x = 1), where the curve is appended to the constant or saturated levels.

  7. Learning curve - Wikipedia

    en.wikipedia.org/wiki/Learning_curve

    The S-Curve or Sigmoid function is the idealized general form of all learning curves, with slowly accumulating small steps at first followed by larger steps and then successively smaller ones later, as the learning activity reaches its limit. That idealizes the normal progression from discovery of something to learn about followed to the limit ...

  8. Autocatalysis - Wikipedia

    en.wikipedia.org/wiki/Autocatalysis

    The graph for these equations is a sigmoid curve (specifically a logistic function), which is typical for autocatalytic reactions: these chemical reactions proceed slowly at the start (the induction period) because there is little catalyst present, the rate of reaction increases progressively as the reaction proceeds as the amount of catalyst ...

  9. Logistic distribution - Wikipedia

    en.wikipedia.org/wiki/Logistic_distribution

    The logistic distribution receives its name from its cumulative distribution function, which is an instance of the family of logistic functions.The cumulative distribution function of the logistic distribution is also a scaled version of the hyperbolic tangent.