Least square method robustness of computations: What is not usually considered and taught
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43952026" target="_blank" >RIV/49777513:23520/17:43952026 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.15439/2017F7" target="_blank" >http://dx.doi.org/10.15439/2017F7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.15439/2017F7" target="_blank" >10.15439/2017F7</a>
Alternative languages
Result language
angličtina
Original language name
Least square method robustness of computations: What is not usually considered and taught
Original language description
There are many practical applications based on the Least Square Error (LSE) approximation. It is based on a square error minimization “on a vertical” axis. The LSE method is simple and easy also for analytical purposes. However, if data span is large over several magnitudes or non-linear LSE is used, severe numerical instability can be expected. The presented contribution describes a simple method for large span of data LSE computation. It is especially convenient if large span of data are to be processed, when the “standard” pseudoinverse matrix is ill conditioned. It is actually based on a LSE solution using orthogonal basis vectors instead of orthonormal basis vectors. The presented approach has been used for a linear regression as well as for approximation using radial basis functions.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA17-05534S" target="_blank" >GA17-05534S: Meshless methods for large scattered spatio-temporal vector data visualization</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Federated Conference on Computer Science and Information Systems,
ISBN
978-1-5090-4414-6
ISSN
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e-ISSN
neuvedeno
Number of pages
5
Pages from-to
537-541
Publisher name
IEEE
Place of publication
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Event location
Praha
Event date
Sep 3, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000417412800080