Self-Organizing Maps:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2001
|
| Ausgabe: | Third Edition |
| Schriftenreihe: | Springer Series in Information Sciences
30 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | The Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. About 4000 research articles on it have appeared in the open literature, and many industrial projects use the SOM as a tool for solving hard real-world problems. Many fields of science have adopted the SOM as a standard analytical tool: in statistics, signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. The SOM solves difficult high-dimensional and nonlinear problems such as feature extraction and classification of images and acoustic patterns, adaptive control of robots, and equalization, demodulation, and error-tolerant transmission of signals in telecommunications. A new area is organization of very large document collections. Last but not least, it may be mentioned that the SOM is one of the most realistic models of the biological brain function. This new edition includes a survey of over 2000 contemporary studies to cover the newest results; case examples were provided with detailed formulae, illustrations, and tables; a new chapter on Software Tools for SOM was written, other chapters were extended or reorganized |
| Beschreibung: | 1 Online-Ressource (XX, 502 p) |
| ISBN: | 9783642569272 9783540679219 |
| ISSN: | 0720-678X |
| DOI: | 10.1007/978-3-642-56927-2 |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV042413250 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 150316s2001 |||| o||u| ||||||eng d | ||
| 020 | |a 9783642569272 |c Online |9 978-3-642-56927-2 | ||
| 020 | |a 9783540679219 |c Print |9 978-3-540-67921-9 | ||
| 024 | 7 | |a 10.1007/978-3-642-56927-2 |2 doi | |
| 035 | |a (OCoLC)863735879 | ||
| 035 | |a (DE-599)BVBBV042413250 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-91 |a DE-83 | ||
| 082 | 0 | |a 621 |2 23 | |
| 084 | |a PHY 000 |2 stub | ||
| 100 | 1 | |a Kohonen, Teuvo |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Self-Organizing Maps |c by Teuvo Kohonen |
| 250 | |a Third Edition | ||
| 264 | 1 | |a Berlin, Heidelberg |b Springer Berlin Heidelberg |c 2001 | |
| 300 | |a 1 Online-Ressource (XX, 502 p) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Springer Series in Information Sciences |v 30 |x 0720-678X | |
| 500 | |a The Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. About 4000 research articles on it have appeared in the open literature, and many industrial projects use the SOM as a tool for solving hard real-world problems. Many fields of science have adopted the SOM as a standard analytical tool: in statistics, signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. The SOM solves difficult high-dimensional and nonlinear problems such as feature extraction and classification of images and acoustic patterns, adaptive control of robots, and equalization, demodulation, and error-tolerant transmission of signals in telecommunications. A new area is organization of very large document collections. Last but not least, it may be mentioned that the SOM is one of the most realistic models of the biological brain function. This new edition includes a survey of over 2000 contemporary studies to cover the newest results; case examples were provided with detailed formulae, illustrations, and tables; a new chapter on Software Tools for SOM was written, other chapters were extended or reorganized | ||
| 650 | 4 | |a Physics | |
| 650 | 4 | |a Telecommunication | |
| 650 | 4 | |a Statistical Physics, Dynamical Systems and Complexity | |
| 650 | 4 | |a Biophysics and Biological Physics | |
| 650 | 4 | |a Communications Engineering, Networks | |
| 650 | 0 | 7 | |a Selbstorganisierende Karte |0 (DE-588)4305302-6 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Selbstorganisierende Karte |0 (DE-588)4305302-6 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-642-56927-2 |x Verlag |3 Volltext |
| 912 | |a ZDB-2-PHA |a ZDB-2-BAE | ||
| 940 | 1 | |q ZDB-2-PHA_Archive | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-027848743 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
Datensatz im Suchindex
| _version_ | 1804153077255634944 |
|---|---|
| any_adam_object | |
| author | Kohonen, Teuvo |
| author_facet | Kohonen, Teuvo |
| author_role | aut |
| author_sort | Kohonen, Teuvo |
| author_variant | t k tk |
| building | Verbundindex |
| bvnumber | BV042413250 |
| classification_tum | PHY 000 |
| collection | ZDB-2-PHA ZDB-2-BAE |
| ctrlnum | (OCoLC)863735879 (DE-599)BVBBV042413250 |
| dewey-full | 621 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 621 - Applied physics |
| dewey-raw | 621 |
| dewey-search | 621 |
| dewey-sort | 3621 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Physik |
| doi_str_mv | 10.1007/978-3-642-56927-2 |
| edition | Third Edition |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02888nmm a2200481zcb4500</leader><controlfield tag="001">BV042413250</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">150316s2001 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783642569272</subfield><subfield code="c">Online</subfield><subfield code="9">978-3-642-56927-2</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783540679219</subfield><subfield code="c">Print</subfield><subfield code="9">978-3-540-67921-9</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-3-642-56927-2</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)863735879</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV042413250</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-91</subfield><subfield code="a">DE-83</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">621</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">PHY 000</subfield><subfield code="2">stub</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kohonen, Teuvo</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Self-Organizing Maps</subfield><subfield code="c">by Teuvo Kohonen</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">Third Edition</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Berlin, Heidelberg</subfield><subfield code="b">Springer Berlin Heidelberg</subfield><subfield code="c">2001</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (XX, 502 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">Springer Series in Information Sciences</subfield><subfield code="v">30</subfield><subfield code="x">0720-678X</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">The Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. About 4000 research articles on it have appeared in the open literature, and many industrial projects use the SOM as a tool for solving hard real-world problems. Many fields of science have adopted the SOM as a standard analytical tool: in statistics, signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. The SOM solves difficult high-dimensional and nonlinear problems such as feature extraction and classification of images and acoustic patterns, adaptive control of robots, and equalization, demodulation, and error-tolerant transmission of signals in telecommunications. A new area is organization of very large document collections. Last but not least, it may be mentioned that the SOM is one of the most realistic models of the biological brain function. This new edition includes a survey of over 2000 contemporary studies to cover the newest results; case examples were provided with detailed formulae, illustrations, and tables; a new chapter on Software Tools for SOM was written, other chapters were extended or reorganized</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Physics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Telecommunication</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistical Physics, Dynamical Systems and Complexity</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Biophysics and Biological Physics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Communications Engineering, Networks</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Selbstorganisierende Karte</subfield><subfield code="0">(DE-588)4305302-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Selbstorganisierende Karte</subfield><subfield code="0">(DE-588)4305302-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-3-642-56927-2</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-PHA</subfield><subfield code="a">ZDB-2-BAE</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-PHA_Archive</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-027848743</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield></record></collection> |
| id | DE-604.BV042413250 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:20:52Z |
| institution | BVB |
| isbn | 9783642569272 9783540679219 |
| issn | 0720-678X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027848743 |
| oclc_num | 863735879 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM DE-83 |
| owner_facet | DE-91 DE-BY-TUM DE-83 |
| physical | 1 Online-Ressource (XX, 502 p) |
| psigel | ZDB-2-PHA ZDB-2-BAE ZDB-2-PHA_Archive |
| publishDate | 2001 |
| publishDateSearch | 2001 |
| publishDateSort | 2001 |
| publisher | Springer Berlin Heidelberg |
| record_format | marc |
| series2 | Springer Series in Information Sciences |
| spelling | Kohonen, Teuvo Verfasser aut Self-Organizing Maps by Teuvo Kohonen Third Edition Berlin, Heidelberg Springer Berlin Heidelberg 2001 1 Online-Ressource (XX, 502 p) txt rdacontent c rdamedia cr rdacarrier Springer Series in Information Sciences 30 0720-678X The Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. About 4000 research articles on it have appeared in the open literature, and many industrial projects use the SOM as a tool for solving hard real-world problems. Many fields of science have adopted the SOM as a standard analytical tool: in statistics, signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. The SOM solves difficult high-dimensional and nonlinear problems such as feature extraction and classification of images and acoustic patterns, adaptive control of robots, and equalization, demodulation, and error-tolerant transmission of signals in telecommunications. A new area is organization of very large document collections. Last but not least, it may be mentioned that the SOM is one of the most realistic models of the biological brain function. This new edition includes a survey of over 2000 contemporary studies to cover the newest results; case examples were provided with detailed formulae, illustrations, and tables; a new chapter on Software Tools for SOM was written, other chapters were extended or reorganized Physics Telecommunication Statistical Physics, Dynamical Systems and Complexity Biophysics and Biological Physics Communications Engineering, Networks Selbstorganisierende Karte (DE-588)4305302-6 gnd rswk-swf Selbstorganisierende Karte (DE-588)4305302-6 s 1\p DE-604 https://doi.org/10.1007/978-3-642-56927-2 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Kohonen, Teuvo Self-Organizing Maps Physics Telecommunication Statistical Physics, Dynamical Systems and Complexity Biophysics and Biological Physics Communications Engineering, Networks Selbstorganisierende Karte (DE-588)4305302-6 gnd |
| subject_GND | (DE-588)4305302-6 |
| title | Self-Organizing Maps |
| title_auth | Self-Organizing Maps |
| title_exact_search | Self-Organizing Maps |
| title_full | Self-Organizing Maps by Teuvo Kohonen |
| title_fullStr | Self-Organizing Maps by Teuvo Kohonen |
| title_full_unstemmed | Self-Organizing Maps by Teuvo Kohonen |
| title_short | Self-Organizing Maps |
| title_sort | self organizing maps |
| topic | Physics Telecommunication Statistical Physics, Dynamical Systems and Complexity Biophysics and Biological Physics Communications Engineering, Networks Selbstorganisierende Karte (DE-588)4305302-6 gnd |
| topic_facet | Physics Telecommunication Statistical Physics, Dynamical Systems and Complexity Biophysics and Biological Physics Communications Engineering, Networks Selbstorganisierende Karte |
| url | https://doi.org/10.1007/978-3-642-56927-2 |
| work_keys_str_mv | AT kohonenteuvo selforganizingmaps |