Evolutionary learning of regularization networks with product kernel units

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F11%3A00369174" target="_blank" >RIV/67985807:_____/11:00369174 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICSMC.2011.6083783" target="_blank" >http://dx.doi.org/10.1109/ICSMC.2011.6083783</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICSMC.2011.6083783" target="_blank" >10.1109/ICSMC.2011.6083783</a>

Result language
angličtina
Original language name
Evolutionary learning of regularization networks with product kernel units
Original language description
This paper deals with learning possibilities of regularization networks with product kernel units. Approximation problems formulated as regularized minimization problems with kernel-based stabilizers lead to solutions of the shape of linear combination of kernel functions. These can be expressed as one-hidden layer feed-forward neural network schemes, called regularization networks. We propose a novel evolutionary algorithm utilizing for regularization networks with product kernels. This algorithm utilizes genetic search for suitable network parameters as well as kernel functions.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)