SMOOS — A program for the filtration of non-stationary statistical series

Published: 1 January 1981| Version 1 | DOI: 10.17632/wgdf2gntdn.1
V.B. Zlokazov


Abstract A method is described for constructing numerical high and low frequency filters for the filtration of the trajectories of strongly non-stationary stochastic processes (e.g. with a trend of the type of resonance functions). Measures of function oscillations and function variability are introduced, and by making use of them the problem of constructing the above-mentioned filters is formulated in terms of the calculus of variations. A compact algorithm for the numerical implementation of the met... Title of program: SMOOS,SMOSI Catalogue Id: ABVQ_v1_0 Nature of problem The program either smoothes a statistical series with a strongly non- stationary (e.g. resonance-like) trend or extracts from it a low frequency envelope from below. Versions of this program held in the CPC repository in Mendeley Data ABVQ_v1_0; SMOOS,SMOSI; 10.1016/0010-4655(81)90014-X This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)



Computational Physics, Computational Method