Higher Order Neural Networks: Fundamental Theory and Applications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F10%3A00170252" target="_blank" >RIV/68407700:21220/10:00170252 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Higher Order Neural Networks: Fundamental Theory and Applications
Original language description
n this chapter, we provide fundamental principles of higher order neural units (HONUs) and higher order neural networks (HONNs). An essential core of HONNs can be found in higher order weighted combinations or correlations between the input variables. Byusing some typical examples, this chapter describes how and why higher order combinations or correlations can be effective.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
BC - Theory and management systems
OECD FORD branch
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Result continuities
Project
<a href="/en/project/2B06023" target="_blank" >2B06023: Development of a method for estimation of energy and matter fluxes in selected ecosystems; formulation and verification of principles for evaluation of conditions supporting selfregulation and biodiversity.</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications
ISBN
978-1-61520-712-1
Number of pages of the result
26
Pages from-to
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Number of pages of the book
634
Publisher name
IGI Publishing
Place of publication
Hershey
UT code for WoS chapter
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