Creator:

Stanisławski, Rafał ; Latawiec, Krzysztof J.

Contributor:

Cordón, Oskar - ed. ; Kazienko, Przemysław - ed.

Title:

Normalized finite fractional differences: Computational and accuracy breakthroughs

Subtitle:

Hybrid and Ensemble Methods in Machine Learning

Group publication title:

AMCS, Volume 22 (2012)

Subject and Keywords:

fractional difference ; Grünwald-Letnikov ; difference ; stability analysis ; recursive computation ; adaptive systems

Abstract:

This paper presents a series of new results in finite and infinite-memory modeling of discrete-time fractional differences. The introduced ?normalized finite fractional difference? is shown to properly approximate its fractional difference original, in particular in terms of the steady-state properties. ; A stability analysis is also presented and a recursive computation algorithm is offered for finite fractional differences. A thorough analysis of computational and accuracy aspects is culminated with the introduction of a ?perfect finite fractional difference? and, in particular, a powerful ?adaptive finite fractional difference?, whose excellent performance is illustrated in simulation examples.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2012

Resource Type:

artykuł

DOI:

10.2478/v10006-012-0067-9

Pages:

907-919

Source:

AMCS, Volume 22, Number 4 (2012) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego