Convergence Analysis of Recurrent Neural Networks:
Since the outstanding and pioneering research work of Hopfield on recurrent neural networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong interests in scientists and researchers. Recent years have recorded a remarkable advance in research and development work on...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer US
2004
|
| Ausgabe: | 1st ed. 2004 |
| Schriftenreihe: | Network Theory and Applications
13 |
| Schlagworte: | |
| Online-Zugang: | UBY01 Volltext |
| Zusammenfassung: | Since the outstanding and pioneering research work of Hopfield on recurrent neural networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong interests in scientists and researchers. Recent years have recorded a remarkable advance in research and development work on RNNs, both in theoretical research as weIl as actual applications. The field of RNNs is now transforming into a complete and independent subject. From theory to application, from software to hardware, new and exciting results are emerging day after day, reflecting the keen interest RNNs have instilled in everyone, from researchers to practitioners. RNNs contain feedback connections among the neurons, a phenomenon which has led rather naturally to RNNs being regarded as dynamical systems. RNNs can be described by continuous time differential systems, discrete time systems, or functional differential systems, and more generally, in terms of non linear systems. Thus, RNNs have to their disposal, a huge set of mathematical tools relating to dynamical system theory which has tumed out to be very useful in enabling a rigorous analysis of RNNs |
| Beschreibung: | 1 Online-Ressource (XVII, 233 p) |
| ISBN: | 9781475738193 |
| DOI: | 10.1007/978-1-4757-3819-3 |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV047064248 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 201216s2004 |||| o||u| ||||||eng d | ||
| 020 | |a 9781475738193 |9 978-1-4757-3819-3 | ||
| 024 | 7 | |a 10.1007/978-1-4757-3819-3 |2 doi | |
| 035 | |a (ZDB-2-SCS)978-1-4757-3819-3 | ||
| 035 | |a (OCoLC)1227478627 | ||
| 035 | |a (DE-599)BVBBV047064248 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-706 | ||
| 082 | 0 | |a 004.0151 |2 23 | |
| 100 | 0 | |a Zhang Yi |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Convergence Analysis of Recurrent Neural Networks |c by Zhang Yi |
| 250 | |a 1st ed. 2004 | ||
| 264 | 1 | |a New York, NY |b Springer US |c 2004 | |
| 300 | |a 1 Online-Ressource (XVII, 233 p) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Network Theory and Applications |v 13 | |
| 520 | |a Since the outstanding and pioneering research work of Hopfield on recurrent neural networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong interests in scientists and researchers. Recent years have recorded a remarkable advance in research and development work on RNNs, both in theoretical research as weIl as actual applications. The field of RNNs is now transforming into a complete and independent subject. From theory to application, from software to hardware, new and exciting results are emerging day after day, reflecting the keen interest RNNs have instilled in everyone, from researchers to practitioners. RNNs contain feedback connections among the neurons, a phenomenon which has led rather naturally to RNNs being regarded as dynamical systems. RNNs can be described by continuous time differential systems, discrete time systems, or functional differential systems, and more generally, in terms of non linear systems. Thus, RNNs have to their disposal, a huge set of mathematical tools relating to dynamical system theory which has tumed out to be very useful in enabling a rigorous analysis of RNNs | ||
| 650 | 4 | |a Mathematics of Computing | |
| 650 | 4 | |a Systems Theory, Control | |
| 650 | 4 | |a Electrical Engineering | |
| 650 | 4 | |a Computer science—Mathematics | |
| 650 | 4 | |a System theory | |
| 650 | 4 | |a Electrical engineering | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781475738216 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781402076947 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781475738209 |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-1-4757-3819-3 |x Verlag |z URL des Eerstveröffentlichers |3 Volltext |
| 912 | |a ZDB-2-SCS | ||
| 940 | 1 | |q ZDB-2-SCS_2000/2004 | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-032471360 | ||
| 966 | e | |u https://doi.org/10.1007/978-1-4757-3819-3 |l UBY01 |p ZDB-2-SCS |q ZDB-2-SCS_2000/2004 |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804182062004961280 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Zhang Yi |
| author_facet | Zhang Yi |
| author_role | aut |
| author_sort | Zhang Yi |
| author_variant | z y zy |
| building | Verbundindex |
| bvnumber | BV047064248 |
| collection | ZDB-2-SCS |
| ctrlnum | (ZDB-2-SCS)978-1-4757-3819-3 (OCoLC)1227478627 (DE-599)BVBBV047064248 |
| dewey-full | 004.0151 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 004 - Computer science |
| dewey-raw | 004.0151 |
| dewey-search | 004.0151 |
| dewey-sort | 14.0151 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| doi_str_mv | 10.1007/978-1-4757-3819-3 |
| edition | 1st ed. 2004 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02823nmm a2200481zcb4500</leader><controlfield tag="001">BV047064248</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">201216s2004 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781475738193</subfield><subfield code="9">978-1-4757-3819-3</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-1-4757-3819-3</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-2-SCS)978-1-4757-3819-3</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1227478627</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047064248</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-706</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">004.0151</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Zhang Yi</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Convergence Analysis of Recurrent Neural Networks</subfield><subfield code="c">by Zhang Yi</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed. 2004</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, NY</subfield><subfield code="b">Springer US</subfield><subfield code="c">2004</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (XVII, 233 p)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Network Theory and Applications</subfield><subfield code="v">13</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Since the outstanding and pioneering research work of Hopfield on recurrent neural networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong interests in scientists and researchers. Recent years have recorded a remarkable advance in research and development work on RNNs, both in theoretical research as weIl as actual applications. The field of RNNs is now transforming into a complete and independent subject. From theory to application, from software to hardware, new and exciting results are emerging day after day, reflecting the keen interest RNNs have instilled in everyone, from researchers to practitioners. RNNs contain feedback connections among the neurons, a phenomenon which has led rather naturally to RNNs being regarded as dynamical systems. RNNs can be described by continuous time differential systems, discrete time systems, or functional differential systems, and more generally, in terms of non linear systems. Thus, RNNs have to their disposal, a huge set of mathematical tools relating to dynamical system theory which has tumed out to be very useful in enabling a rigorous analysis of RNNs</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematics of Computing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Systems Theory, Control</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Electrical Engineering</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer science—Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">System theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Electrical engineering</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9781475738216</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9781402076947</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9781475738209</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-1-4757-3819-3</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Eerstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SCS</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SCS_2000/2004</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-032471360</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4757-3819-3</subfield><subfield code="l">UBY01</subfield><subfield code="p">ZDB-2-SCS</subfield><subfield code="q">ZDB-2-SCS_2000/2004</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV047064248 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:12:22Z |
| indexdate | 2024-07-10T09:01:34Z |
| institution | BVB |
| isbn | 9781475738193 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032471360 |
| oclc_num | 1227478627 |
| open_access_boolean | |
| owner | DE-706 |
| owner_facet | DE-706 |
| physical | 1 Online-Ressource (XVII, 233 p) |
| psigel | ZDB-2-SCS ZDB-2-SCS_2000/2004 ZDB-2-SCS ZDB-2-SCS_2000/2004 |
| publishDate | 2004 |
| publishDateSearch | 2004 |
| publishDateSort | 2004 |
| publisher | Springer US |
| record_format | marc |
| series2 | Network Theory and Applications |
| spelling | Zhang Yi Verfasser aut Convergence Analysis of Recurrent Neural Networks by Zhang Yi 1st ed. 2004 New York, NY Springer US 2004 1 Online-Ressource (XVII, 233 p) txt rdacontent c rdamedia cr rdacarrier Network Theory and Applications 13 Since the outstanding and pioneering research work of Hopfield on recurrent neural networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong interests in scientists and researchers. Recent years have recorded a remarkable advance in research and development work on RNNs, both in theoretical research as weIl as actual applications. The field of RNNs is now transforming into a complete and independent subject. From theory to application, from software to hardware, new and exciting results are emerging day after day, reflecting the keen interest RNNs have instilled in everyone, from researchers to practitioners. RNNs contain feedback connections among the neurons, a phenomenon which has led rather naturally to RNNs being regarded as dynamical systems. RNNs can be described by continuous time differential systems, discrete time systems, or functional differential systems, and more generally, in terms of non linear systems. Thus, RNNs have to their disposal, a huge set of mathematical tools relating to dynamical system theory which has tumed out to be very useful in enabling a rigorous analysis of RNNs Mathematics of Computing Systems Theory, Control Electrical Engineering Computer science—Mathematics System theory Electrical engineering Erscheint auch als Druck-Ausgabe 9781475738216 Erscheint auch als Druck-Ausgabe 9781402076947 Erscheint auch als Druck-Ausgabe 9781475738209 https://doi.org/10.1007/978-1-4757-3819-3 Verlag URL des Eerstveröffentlichers Volltext |
| spellingShingle | Zhang Yi Convergence Analysis of Recurrent Neural Networks Mathematics of Computing Systems Theory, Control Electrical Engineering Computer science—Mathematics System theory Electrical engineering |
| title | Convergence Analysis of Recurrent Neural Networks |
| title_auth | Convergence Analysis of Recurrent Neural Networks |
| title_exact_search | Convergence Analysis of Recurrent Neural Networks |
| title_exact_search_txtP | Convergence Analysis of Recurrent Neural Networks |
| title_full | Convergence Analysis of Recurrent Neural Networks by Zhang Yi |
| title_fullStr | Convergence Analysis of Recurrent Neural Networks by Zhang Yi |
| title_full_unstemmed | Convergence Analysis of Recurrent Neural Networks by Zhang Yi |
| title_short | Convergence Analysis of Recurrent Neural Networks |
| title_sort | convergence analysis of recurrent neural networks |
| topic | Mathematics of Computing Systems Theory, Control Electrical Engineering Computer science—Mathematics System theory Electrical engineering |
| topic_facet | Mathematics of Computing Systems Theory, Control Electrical Engineering Computer science—Mathematics System theory Electrical engineering |
| url | https://doi.org/10.1007/978-1-4757-3819-3 |
| work_keys_str_mv | AT zhangyi convergenceanalysisofrecurrentneuralnetworks |