Fast Hardware Implementation of NNSU Separating Algorithm

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F14%3A00446430" target="_blank" >RIV/67985807:_____/14:00446430 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/RTC.2014.7097405" target="_blank" >http://dx.doi.org/10.1109/RTC.2014.7097405</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/RTC.2014.7097405" target="_blank" >10.1109/RTC.2014.7097405</a>

Result language
angličtina
Original language name
Fast Hardware Implementation of NNSU Separating Algorithm
Original language description
This paper has two objectives. First, we introduce a separation algorithm of a neural network with switching units (NNSU), and present its applicability to processing selected MonteCarlo (MC) data channels of the LHC detector in CERN Geneve and selectedMC data of DO-detector in FNAL. The result achieved by this algorithm provides better separation of signal and background events than classical cut-based methods and the separation result is comparable to TMVA ROOT methods, such as BDT and MLP. The training phase of NNSU uses a genetic optimization of NNSU architecture, hence a convenient definition of corresponding fitness function allows for refinement of separation results to meet user defined requirements. In the next parts we discuss the possibility of efficient hardware implementation. NNSU algorithm is in fact a piecewise linear discrimination and, therefore, testing phase of the algorithm can be performed by hardware means. First step toward hardware implementation was done, and
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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