METHOD OF SET AND TAXONOMY INDUCTION OF CYCLIC FUNCTIONAL RELATIONS CLASSES WITHIN THE FRAMEWORK OF AXIOMATIC-DEDUCTIVE STRATEGY OF ORGANIZATION OF CYCLIC FUNCTIONAL RELATIONS THEORY
Abstract
The paper defines the classes of cyclic functional relations and their taxonomy, which allowed to formalize and organize the theory according to the axiomatic-deductive strategy. A set of cyclic attributes, a set of domains of definition, a set of types of rhythm of cyclic functional relation are formed, which forms a taxonomy of models of cyclic signals, which in turn are a component of the theory of cyclic functional relations.
A method for generating a set and taxonomy of classes of cyclic functional relations has been developed. The taxonomy of models’ classes, methods, algorithms and software for processing and simulation (generation) of cyclic signals within the theory of cyclic functional relations is developed.
Keywords: induction method, class taxonomy, cyclic functional relations, axiomatic-deductive strategy.
Full Text:
PDFReferences
Gardner W. A. (2005) Cyclostationarity: Half a century of research. W. A. Gardner, A. Napolitano, L. Paura. Signal Processing. № 86 (2006). P. 639-697.
Hurd H. L. (2001) Periodically Correlated Random Sequences: Spectral Theory and Practice. H. L. Hurd, The University of North Carolina at Chapel Hill Hampton University
Kochel P. (1980) Periodically stationary Markovian decision models. P. Kochel. Elektron. Informationsverarb. Kybernet. No. 16. P. 553-567 (in German).
Nematollahi A. R. (2000) Discrete time periodically correlated Markov processes. A. R. Nematollahi , A. R. Soltani. Probability and Mathematical Statistics. No. 20 (1). P. 127-140.
Ghysels E. (1993) Bayesian Inference for a General Class of Periodic Markov Switching Models. E. Ghysels, R. E. McCulloch, R. S. Tsay. 1993.
Ghysels E. (1992) On the Periodic Structure of the Business Cycle. E. Ghysels. Cowles Foundation, Yale Universiti. No. 1028.
Bittanti S. (1991) Markovian representations of cyclostationary processes, in: L. Gerencser, P.E. Caines (Eds.). S. Bittanti, F. Lorito, S. Strada. Topics in Stochastic Systems: Modelling, Estimation and Adaptive Control. Springer, Berlin, Germany. Vol. 161. P. 31-46.
Lupenko S.A. (2016) Teoretychni osnovy modeliuvannia ta opratsiuvannia tsyklichnykh syhnaliv v informatsiinykh systemakh. Naukova monohrafiia. S.A.Lupenko. Lviv. Vydavnytstvo «Mahnoliia 2006», 344 s..
Lupenko S. (2015) Cyclic Linear Random Process As A Mathematical Model Of Cyclic Signals. S. Lupenko, N. Lutsyk, Y. Lapusta. Acta mechanica et automatic. №9(4). pp. 219-224.
Lupenko S. (2018) Modeling and signals processing using cyclic random functions/ A. Lupenko, O. Orobchuk, N. Stadnik, A. Zozulya. 13th IEEE International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), September 11-14. Lviv, Ukraine,T. 1, pp. 360-363. ISBN 978-1-5386-6463-6. IEEE Catalog Number: CFP18D36-PRT.
DOI: https://doi.org/10.26886/2414-634X.4(48)2021.7
Refbacks
- There are currently no refbacks.