Logistic Sigmoid Function

From GM-RKB
(Redirected from Logistic)
Jump to navigation Jump to search

A Logistic Sigmoid Function is a sigmoid exponential probability function of the form [math]\displaystyle{ f(t,A,B,C) \equiv (C + Ae^{-Bt})^{-1} }[/math].



References

2018

2018

  • (Wikipedia, 2018) ⇒ https://en.wikipedia.org/wiki/logistic_function#Mathematical_properties Retrieved:2018-2-4.
    • The standard logistic function is the logistic function with parameters (k = 1, x0 = 0, L = 1) which yields : [math]\displaystyle{ \begin{align} f(x) &= \frac{1}{1 + e^{-x}} \\ &= \frac{e^x}{1 + e^x} \\ &= \tfrac12 + \tfrac12 \tanh(\tfrac{x}{2}) \\ \end{align} }[/math] In practice, due to the nature of the exponential function ex, it is often sufficient to compute the standard logistic function for x over a small range of real numbers such as a range contained in [−6, +6].

      The logistic function has the symmetry property that: : [math]\displaystyle{ 1-f(x) = f(-x). }[/math] Thus, [math]\displaystyle{ x \mapsto f(x) - 1/2 }[/math] is an odd function.

      The logistic function is an offset and scaled hyperbolic tangent function : [math]\displaystyle{ f(x) = \tfrac12 + \tfrac12 \tanh(\tfrac{x}{2}) }[/math] or : [math]\displaystyle{ \tanh(x) = 2 \, f(2x) - 1 }[/math] .

      This follows from : [math]\displaystyle{ \begin{align} \tanh(x) & = \frac{e^x - e^{-x}}{e^x + e^{-x}} = \frac{e^x \cdot \left(1 - e^{-2x}\right)}{e^x \cdot \left(1 + e^{-2x}\right)} \\[6pt] & = f(2x) - \frac{e^{-2x}}{1+e^{-2x}} = f(2x) - \frac{e^{-2x} + 1 - 1}{1+e^{-2x}} = 2f(2x)-1. \end{align} }[/math]

2013

2009