Current Derivative Estimation of Non-stationary Processes Based on Metrical Information; Computational Collective Intelligence; Vol. 9330 of the series Lecture Notes in Computer Science

Current Derivative Estimation of Non-stationary Processes Based on Metrical Information; Computational Collective Intelligence; Vol. 9330 of the series Lecture Notes in Computer Science

Bibliographic Details
Parent link:Computational Collective Intelligence
Vol. 9330 of the series Lecture Notes in Computer Science.— 2015.— [P. 512-519]
Main Author: Kochegurova E. A. Elena Alekseevna
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра автоматики и компьютерных систем (АИКС)
Other Authors: Gorokhova E. Ekaterina
Summary:Title screen
Demand for estimation of derivatives has arisen in a range of some applied problems. One of the possible approaches to estimating derivatives is to approximate measurement data. The problem of real-time estimation of de-rivatives is investigated. A variation method of obtaining recurrent smoothing splines is proposed for estimation of derivatives. A distinguishing feature of the described method is recurrence of spline coefficients with respect to its segments and locality about measured values inside the segment. Influence of smoothing spline parameters on efficiency of such estimations is studied. Comparative analysis of experimental results is performed.
Режим доступа: по договору с организацией-держателем ресурса
Language:English
Published: 2015
Subjects:
электронный ресурс
труды учёных ТПУ
рекуррентные алгоритмы
производные
сплайны
Online Access:http://dx.doi.org/10.1007/978-3-319-24306-1_50
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=645945

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