dorsal/arxiv
View SchemaA Hardware Implementation of Artificial Neural Network Using Field Programmable Gate Arrays
| Authors | E. Won |
|---|---|
| Categories | |
| ArXiv ID | physics/0703041 |
| URL | https://arxiv.org/abs/physics/0703041 |
| DOI | 10.1016/j.nima.2007.08.163 |
Abstract
An artificial neural network algorithm is implemented using a field programmable gate array hardware. One hidden layer is used in the feed-forward neural network structure in order to discriminate one class of patterns from the other class in real time. With five 8-bit input patterns, six hidden nodes, and one 8-bit output, the implemented hardware neural network makes decision on a set of input patterns in 11 clocks and the result is identical to what to expect from off-line computation. This implementation may be used in level 1 hardware triggers in high energy physics experiments
{
"annotation_id": "3549f584-4d80-4c98-99a8-f211fe7f6a53",
"date_created": "2026-03-02T18:01:17.763000Z",
"date_modified": "2026-03-02T18:01:17.763000Z",
"file_hash": "ab3245a10d3da8096ce3e2efc3c951414e5b1459286331813e4fb349ce5d166b",
"private": false,
"record": {
"abstract": "An artificial neural network algorithm is implemented using a field\nprogrammable gate array hardware. One hidden layer is used in the feed-forward\nneural network structure in order to discriminate one class of patterns from\nthe other class in real time. With five 8-bit input patterns, six hidden nodes,\nand one 8-bit output, the implemented hardware neural network makes decision on\na set of input patterns in 11 clocks and the result is identical to what to\nexpect from off-line computation. This implementation may be used in level 1\nhardware triggers in high energy physics experiments",
"arxiv_id": "physics/0703041",
"authors": [
"E. Won"
],
"categories": [
"physics.ins-det"
],
"doi": "10.1016/j.nima.2007.08.163",
"title": "A Hardware Implementation of Artificial Neural Network Using Field Programmable Gate Arrays",
"url": "https://arxiv.org/abs/physics/0703041"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "d05824b9-1602-4ad6-b089-9f50077b1fce",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}