Real-time gamma-neutron discrimination with a trainable polynomial kernel

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F25%3A00142732" target="_blank" >RIV/00216224:14330/25:00142732 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1051/epjconf/202533810004" target="_blank" >http://dx.doi.org/10.1051/epjconf/202533810004</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1051/epjconf/202533810004" target="_blank" >10.1051/epjconf/202533810004</a>

Result language

angličtina

Original language name

Real-time gamma-neutron discrimination with a trainable polynomial kernel

Original language description

This paper presents an implementation of gamma-neutron pulse shape discrimination by a support vector machine polynomial decision function in a field-programmable gate array. The training is carried out on a conventional computer using widespread Python libraries. The hardware architecture is designed to allow parameter changes on demand, enabling tuning of hyperparameters and kernel coefficients without requiring re-synthesis. A cubic kernel is compared against a linear kernel which was developed alongside it for non-biased comparison. Both are designed to be viable for real-time classification. The particularities of the designs are explored. The cubic kernel makes use of two stand-alone state machines to keep the sequential data pipelined without interference between the sampled pulses. The results show the trade-off between separation quality, numerical accuracy and physical on-board requirements of the implementations. The separation quality is demonstrated on two datasets, one with a noticeable overlap, to assess any benefits the cubic kernel may bring.

Czech name

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Czech description

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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)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

EPJ Web Conf. Volume 338, 2025 ANIMMA 2025 – Advancements in Nuclear Instrumentation Measurement Methods and their Applications

ISBN

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ISSN

2101-6275

e-ISSN

2100-014X

Number of pages

7

Pages from-to

1-7

Publisher name

EDP Sciences

Place of publication

Les Ulis

Event location

Valencie, Španělsko

Event date

Jun 9, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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