Open AccessEfficient approximation for linear and non‐linear signal representation
Author(s) -
Bilgehan Bülent
Publication year - 2015
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2014.0070
Subject(s) - representation (politics) , signal processing , computer science , algorithm , multiplicative noise , multiplicative function , range (aeronautics) , computation , linear filter , parametric statistics , image processing , signal (programming language) , linear map , field (mathematics) , linear model , linear system , exponential function , artificial intelligence , mathematics , digital signal processing , image (mathematics) , analog signal , computer vision , filter (signal processing) , signal transfer function , machine learning , statistics , materials science , law , mathematical analysis , composite material , political science , programming language , politics , pure mathematics , computer hardware
This paper focuses on optimum representation for both linear and non‐linear type signals which have a wide range of applications in the analysis and processing of real‐world signals, that is, noise, filtering, audio, image etc. Accurate representation of signals, usually is not an easy process. The optimum representation is achieved by introducing exponential bases within multiplicative calculus which enables direct processing to reveal the unknown fitting parameters. Simulation tests confirm that the newly introduced models produce accurate results while using substantially less computation and provide support for applying the new model in the field of parametric linear, non‐linear signal representation for processing.