On Monotonic Radial Basis Function Networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00363278" target="_blank" >RIV/68407700:21230/24:00363278 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/TCYB.2022.3185827" target="_blank" >https://doi.org/10.1109/TCYB.2022.3185827</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TCYB.2022.3185827" target="_blank" >10.1109/TCYB.2022.3185827</a>

Result language
angličtina
Original language name
On Monotonic Radial Basis Function Networks
Original language description
This article deals with monotonicity conditions for radial basis function (RBF) networks. Two architectures of RBF networks are considered-1) unnormalized network with a local character of the basis function and 2) a normalized network where the value of RBF is taken relatively with respect to the others. Different approaches are followed for each of them. For the former, monotonicity is enforced in prescribed points whereas for the latter sufficient monotonicity conditions are formulated. In both cases, the monotonicity conditions are expressed as linear constraints on the network weights that enable efficient solving of the related optimization problems. Many illustrative examples are presented to show the advantages of incorporating prior information in the form of monotonicity.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20205 - Automation and control systems

Project
<a href="/en/project/GA18-26278S" target="_blank" >GA18-26278S: Incorporation of Prior Knowledge for Identification of Nonlinear Systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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