Ontology type: schema:ScholarlyArticle
2012-01
AUTHORSO. M. Kwon, S. M. Lee, J. H. Park
ABSTRACTIn this paper, the problem of passivity analysis for uncertain neural networks with time-varying delays is considered. By constructing an augmented Lyapunov–Krasovskii’s functional and some novel analysis techniques, improved delay-dependent criteria for checking the passivity of the neural networks are established. The proposed criteria are represented in terms of LMIs (linear matrix inequalities) which can be easily solved by various convex optimization algorithms. Two numerical examples are included to show the superiority of our results. More... »
PAGES1261-1271
http://scigraph.springernature.com/pub.10.1007/s11071-011-0067-6
DOIhttp://dx.doi.org/10.1007/s11071-011-0067-6
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1016271754
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0802",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Computation Theory and Mathematics",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Information and Computing Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Chungbuk National University",
"id": "https://www.grid.ac/institutes/grid.254229.a",
"name": [
"School of Electrical Engineering, Chungbuk National University, 52 Naesudong-ro, Heungduk-gu, 361-763, Cheongju, Republic of Korea"
],
"type": "Organization"
},
"familyName": "Kwon",
"givenName": "O. M.",
"id": "sg:person.01337000762.48",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01337000762.48"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Daegu University",
"id": "https://www.grid.ac/institutes/grid.412077.7",
"name": [
"Department of Electronic Engineering, Daegu University, 712-714, Gyungsan, Republic of Korea"
],
"type": "Organization"
},
"familyName": "Lee",
"givenName": "S. M.",
"id": "sg:person.07615211351.42",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07615211351.42"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Yeungnam University",
"id": "https://www.grid.ac/institutes/grid.413028.c",
"name": [
"Department of Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, 712-749, Kyongsan, Republic of Korea"
],
"type": "Organization"
},
"familyName": "Park",
"givenName": "J. H.",
"id": "sg:person.07705373347.23",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07705373347.23"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1016/j.chaos.2005.04.124",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000440085"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.nahs.2010.07.002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004408966"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/rnc.1384",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004921789"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.automatica.2008.09.010",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1010222442"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.neucom.2009.10.010",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016305285"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11063-009-9116-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020536705",
"https://doi.org/10.1007/s11063-009-9116-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11063-009-9116-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020536705",
"https://doi.org/10.1007/s11063-009-9116-2"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.amc.2008.11.046",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1023148037"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.physleta.2005.05.016",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026953399"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.physleta.2005.05.016",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026953399"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf00276493",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035076039",
"https://doi.org/10.1007/bf00276493"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf00276493",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035076039",
"https://doi.org/10.1007/bf00276493"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.automatica.2009.11.002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035332924"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.physleta.2009.01.047",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044096153"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11063-010-9147-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1049928989",
"https://doi.org/10.1007/s11063-010-9147-8"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11063-010-9147-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1049928989",
"https://doi.org/10.1007/s11063-010-9147-8"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1049/iet-cta:20070325",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1056824992"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tcsii.2004.842050",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061569047"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tcsii.2009.2015399",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061570044"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tnn.2006.881488",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061717096"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tnn.2007.914162",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061717349"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tnn.2008.2002436",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061717420"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tnn.2008.2003980",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061717439"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/cdc.2007.4434619",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093239835"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/cdc.2000.914233",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094583338"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1137/1.9781611970777",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1098556247"
],
"type": "CreativeWork"
}
],
"datePublished": "2012-01",
"datePublishedReg": "2012-01-01",
"description": "In this paper, the problem of passivity analysis for uncertain neural networks with time-varying delays is considered. By constructing an augmented Lyapunov\u2013Krasovskii\u2019s functional and some novel analysis techniques, improved delay-dependent criteria for checking the passivity of the neural networks are established. The proposed criteria are represented in terms of LMIs (linear matrix inequalities) which can be easily solved by various convex optimization algorithms. Two numerical examples are included to show the superiority of our results.",
"genre": "research_article",
"id": "sg:pub.10.1007/s11071-011-0067-6",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1040905",
"issn": [
"0924-090X",
"1573-269X"
],
"name": "Nonlinear Dynamics",
"type": "Periodical"
},
{
"issueNumber": "2",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "67"
}
],
"name": "On improved passivity criteria of uncertain neural networks with time-varying delays",
"pagination": "1261-1271",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"4d88060949d08cc054b187d4ad51e505140a9c0a57dc362f25ccb5cb60fc58f0"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s11071-011-0067-6"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1016271754"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s11071-011-0067-6",
"https://app.dimensions.ai/details/publication/pub.1016271754"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-10T19:08",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8678_00000511.jsonl",
"type": "ScholarlyArticle",
"url": "http://link.springer.com/10.1007%2Fs11071-011-0067-6"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11071-011-0067-6'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11071-011-0067-6'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11071-011-0067-6'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11071-011-0067-6'
This table displays all metadata directly associated to this object as RDF triples.
150 TRIPLES
21 PREDICATES
49 URIs
19 LITERALS
7 BLANK NODES