A family of recurrence generated sigmoidal functions based on the Verhulst logistic function. Some approximation and modelling aspects | Zendy

Nikolay Kyurkchiev | Zendy

Open Access

A family of recurrence generated sigmoidal functions based on the Verhulst logistic function. Some approximation and modelling aspects

Author(s) -

Nikolay Kyurkchiev

Publication year - 2016

Publication title -

biomath communications

Language(s) - English

Resource type - Journals

eISSN - 2367-5241

pISSN - 2367-5233

DOI - 10.11145/bmc.2016.12.171

Subject(s) - heaviside step function , sigmoid function , mathematics , logistic function , hausdorff space , function (biology) , construct (python library) , logistic regression , discrete mathematics , pure mathematics , statistics , computer science , artificial intelligence , evolutionary biology , artificial neural network , biology , programming language

In this note we construct a family of recurrence generated sigmoidal logistic functions based on the Verhulst logistic function. We prove estimates for the Hausdorff approximation of the Heaviside step function by means of this family. Numerical examples, illustrating our results are given.

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