Premium
Generalized probability density function and applications to the experimental data in electrical circuits and systems
Author(s) -
Özyapıcı Ali,
Bilgehan Bülent,
Şensoy Zehra B.
Publication year - 2020
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.2883
Subject(s) - exponential function , probability density function , function (biology) , computer science , probabilistic logic , key (lock) , statistical model , field (mathematics) , algorithm , mathematics , theoretical computer science , artificial intelligence , statistics , mathematical analysis , computer security , evolutionary biology , pure mathematics , biology
Summary The mathematical sciences, and particularly probabilistic and statistical methods, are key to understanding the dependencies of the systems. The purpose of this paper is to encourage a wider recognition by engineers of a new generalized principle which in its mathematical form is a powerful instrument for the solution of practical problems. Generalized probability density function was introduced to permit analysis without pre‐knowledge of the source of the data. The fundamental principles are extended to apply the most related engineering applications without the need to know the type of source generating the data. The generalized model presented eliminates preliminary work in engineering problems. The proposed model introduces an exponential density function to produce a direct solution to randomly varying data. The exponential density function is fully compatible with applications containing randomly distributed data. The success of the generalized model presented is due to the calculated parameters in the exponential density function. The method is applied to various problems chosen from the field of engineering with great success.