sigmoid function

Noun

 * 1)  Any of various real functions whose graph resembles an elongated letter "S"; specifically, the logistic function $$y=\frac {e^x}{e^x+1}=\frac 1 {1+ e^{-x}}$$.
 * 2) * 1995, Jun Han, Claudio Moraga, The Influence of the Sigmoid Function Parameters on the Speed of Backpropagation Learning, José Mira, Francisco Sandoval (editors), From Natural to Artificial Neural Computation: International Workshop on Artificial Neural Networks, Proceedings, Springer, 930, page 195,
 * [The] [s]igmoid function is the most commonly known function used in feed forward neural networks because of its nonlinearity and the computational simplicity of its derivative.
 * 1) * 2016, Roumen Anguelov, Svetoslav Markov, Hausdorff Continuous Interval Functions and Applications, Marco Nehmeier, Jürgen Wolff von Gudenberg, Warwick Tucker (editors), Scientific Computing, Computer Arithmetic, and Validated Numerics: 16th International Symposium, SCAN 2014, Springer, 9553, page 10,
 * Sigmoid functions find multiple applications to neural networks and cell growth population models [14,20]. A sigmoid function on $$\R$$ with a range $$[a,b]$$ is defined as a monotone function $$s(t) : \R \to [a,b]$$ such that $$\textstyle\lim_{t\to-\infty} s(t) = a$$, and $$\textstyle\lim_{t\to\infty} s(t) = b$$.
 * Sigmoid functions find multiple applications to neural networks and cell growth population models [14,20]. A sigmoid function on $$\R$$ with a range $$[a,b]$$ is defined as a monotone function $$s(t) : \R \to [a,b]$$ such that $$\textstyle\lim_{t\to-\infty} s(t) = a$$, and $$\textstyle\lim_{t\to\infty} s(t) = b$$.

Translations

 * German: Sigmoidfunktion