Online learning and adaptive filters:
Learn to solve the unprecedented challenges facing Online Learning and Adaptive Signal Processing in this concise, intuitive text. The ever-increasing amount of data generated every day requires new strategies to tackle issues such as: combining data from a large number of sensors; improving spectra...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge, United Kingdom ; New York, NY, USA
Cambridge University Press
2022
|
| Subjects: | |
| Online Access: | BSB01 BTU01 FHN01 Volltext |
| Summary: | Learn to solve the unprecedented challenges facing Online Learning and Adaptive Signal Processing in this concise, intuitive text. The ever-increasing amount of data generated every day requires new strategies to tackle issues such as: combining data from a large number of sensors; improving spectral usage, utilizing multiple-antennas with adaptive capabilities; or learning from signals placed on graphs, generating unstructured data. Solutions to all of these and more are described in a condensed and unified way, enabling you to expose valuable information from data and signals in a fast and economical way. The up-to-date techniques explained here can be implemented in simple electronic hardware, or as part of multi-purpose systems. Also featuring alternative explanations for online learning, including newly developed methods and data selection, and several easily implemented algorithms, this one-of-a-kind book is an ideal resource for graduate students, researchers, and professionals in online learning and adaptive filtering |
| Item Description: | Title from publisher's bibliographic system (viewed on 24 Nov 2022) |
| Physical Description: | 1 Online-Ressource (xii, 253 Seiten) |
| ISBN: | 9781108896139 |
| DOI: | 10.1017/9781108896139 |
Staff View
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV048665304 | ||
| 003 | DE-604 | ||
| 005 | 20231206 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 230120s2022 |||| o||u| ||||||eng d | ||
| 020 | |a 9781108896139 |c Online |9 978-1-108-89613-9 | ||
| 024 | 7 | |a 10.1017/9781108896139 |2 doi | |
| 035 | |a (ZDB-20-CBO)CR9781108896139 | ||
| 035 | |a (OCoLC)1369566641 | ||
| 035 | |a (DE-599)BVBBV048665304 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-12 |a DE-92 |a DE-634 |a DE-83 | ||
| 082 | 0 | |a 621.3822 | |
| 100 | 1 | |a Diniz, Paulo Sergio Ramirez |d 1956- |0 (DE-588)142917508 |4 aut | |
| 245 | 1 | 0 | |a Online learning and adaptive filters |c Paulo S.R. Diniz [and four others] |
| 264 | 1 | |a Cambridge, United Kingdom ; New York, NY, USA |b Cambridge University Press |c 2022 | |
| 300 | |a 1 Online-Ressource (xii, 253 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Title from publisher's bibliographic system (viewed on 24 Nov 2022) | ||
| 520 | |a Learn to solve the unprecedented challenges facing Online Learning and Adaptive Signal Processing in this concise, intuitive text. The ever-increasing amount of data generated every day requires new strategies to tackle issues such as: combining data from a large number of sensors; improving spectral usage, utilizing multiple-antennas with adaptive capabilities; or learning from signals placed on graphs, generating unstructured data. Solutions to all of these and more are described in a condensed and unified way, enabling you to expose valuable information from data and signals in a fast and economical way. The up-to-date techniques explained here can be implemented in simple electronic hardware, or as part of multi-purpose systems. Also featuring alternative explanations for online learning, including newly developed methods and data selection, and several easily implemented algorithms, this one-of-a-kind book is an ideal resource for graduate students, researchers, and professionals in online learning and adaptive filtering | ||
| 650 | 4 | |a Adaptive signal processing / Mathematics | |
| 650 | 4 | |a Machine learning / Mathematics | |
| 650 | 4 | |a Signal processing / Digital techniques / Mathematics | |
| 650 | 4 | |a Digital filters (Mathematics) | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-1-108-84212-9 |
| 856 | 4 | 0 | |u https://doi.org/10.1017/9781108896139 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-20-CBO | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-034039927 | ||
| 966 | e | |u https://doi.org/10.1017/9781108896139 |l BSB01 |p ZDB-20-CBO |q BSB_PDA_CBO |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1017/9781108896139 |l BTU01 |p ZDB-20-CBO |q BTU_PDA_CBO |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1017/9781108896139 |l FHN01 |p ZDB-20-CBO |q FHN_PDA_CBO |x Verlag |3 Volltext | |
Record in the Search Index
| _version_ | 1804184814782251008 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Diniz, Paulo Sergio Ramirez 1956- |
| author_GND | (DE-588)142917508 |
| author_facet | Diniz, Paulo Sergio Ramirez 1956- |
| author_role | aut |
| author_sort | Diniz, Paulo Sergio Ramirez 1956- |
| author_variant | p s r d psr psrd |
| building | Verbundindex |
| bvnumber | BV048665304 |
| collection | ZDB-20-CBO |
| ctrlnum | (ZDB-20-CBO)CR9781108896139 (OCoLC)1369566641 (DE-599)BVBBV048665304 |
| dewey-full | 621.3822 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 621 - Applied physics |
| dewey-raw | 621.3822 |
| dewey-search | 621.3822 |
| dewey-sort | 3621.3822 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
| discipline_str_mv | Elektrotechnik / Elektronik / Nachrichtentechnik |
| doi_str_mv | 10.1017/9781108896139 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02846nmm a2200433zc 4500</leader><controlfield tag="001">BV048665304</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20231206 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">230120s2022 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781108896139</subfield><subfield code="c">Online</subfield><subfield code="9">978-1-108-89613-9</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1017/9781108896139</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-20-CBO)CR9781108896139</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1369566641</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV048665304</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-12</subfield><subfield code="a">DE-92</subfield><subfield code="a">DE-634</subfield><subfield code="a">DE-83</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">621.3822</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Diniz, Paulo Sergio Ramirez</subfield><subfield code="d">1956-</subfield><subfield code="0">(DE-588)142917508</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Online learning and adaptive filters</subfield><subfield code="c">Paulo S.R. Diniz [and four others]</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge, United Kingdom ; New York, NY, USA</subfield><subfield code="b">Cambridge University Press</subfield><subfield code="c">2022</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xii, 253 Seiten)</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="500" ind1=" " ind2=" "><subfield code="a">Title from publisher's bibliographic system (viewed on 24 Nov 2022)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Learn to solve the unprecedented challenges facing Online Learning and Adaptive Signal Processing in this concise, intuitive text. The ever-increasing amount of data generated every day requires new strategies to tackle issues such as: combining data from a large number of sensors; improving spectral usage, utilizing multiple-antennas with adaptive capabilities; or learning from signals placed on graphs, generating unstructured data. Solutions to all of these and more are described in a condensed and unified way, enabling you to expose valuable information from data and signals in a fast and economical way. The up-to-date techniques explained here can be implemented in simple electronic hardware, or as part of multi-purpose systems. Also featuring alternative explanations for online learning, including newly developed methods and data selection, and several easily implemented algorithms, this one-of-a-kind book is an ideal resource for graduate students, researchers, and professionals in online learning and adaptive filtering</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Adaptive signal processing / Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning / Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Signal processing / Digital techniques / Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Digital filters (Mathematics)</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">978-1-108-84212-9</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1017/9781108896139</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-20-CBO</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034039927</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108896139</subfield><subfield code="l">BSB01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">BSB_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108896139</subfield><subfield code="l">BTU01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">BTU_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108896139</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">FHN_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV048665304 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T21:22:01Z |
| indexdate | 2024-07-10T09:45:19Z |
| institution | BVB |
| isbn | 9781108896139 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034039927 |
| oclc_num | 1369566641 |
| open_access_boolean | |
| owner | DE-12 DE-92 DE-634 DE-83 |
| owner_facet | DE-12 DE-92 DE-634 DE-83 |
| physical | 1 Online-Ressource (xii, 253 Seiten) |
| psigel | ZDB-20-CBO ZDB-20-CBO BSB_PDA_CBO ZDB-20-CBO BTU_PDA_CBO ZDB-20-CBO FHN_PDA_CBO |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Cambridge University Press |
| record_format | marc |
| spelling | Diniz, Paulo Sergio Ramirez 1956- (DE-588)142917508 aut Online learning and adaptive filters Paulo S.R. Diniz [and four others] Cambridge, United Kingdom ; New York, NY, USA Cambridge University Press 2022 1 Online-Ressource (xii, 253 Seiten) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 24 Nov 2022) Learn to solve the unprecedented challenges facing Online Learning and Adaptive Signal Processing in this concise, intuitive text. The ever-increasing amount of data generated every day requires new strategies to tackle issues such as: combining data from a large number of sensors; improving spectral usage, utilizing multiple-antennas with adaptive capabilities; or learning from signals placed on graphs, generating unstructured data. Solutions to all of these and more are described in a condensed and unified way, enabling you to expose valuable information from data and signals in a fast and economical way. The up-to-date techniques explained here can be implemented in simple electronic hardware, or as part of multi-purpose systems. Also featuring alternative explanations for online learning, including newly developed methods and data selection, and several easily implemented algorithms, this one-of-a-kind book is an ideal resource for graduate students, researchers, and professionals in online learning and adaptive filtering Adaptive signal processing / Mathematics Machine learning / Mathematics Signal processing / Digital techniques / Mathematics Digital filters (Mathematics) Erscheint auch als Druck-Ausgabe 978-1-108-84212-9 https://doi.org/10.1017/9781108896139 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Diniz, Paulo Sergio Ramirez 1956- Online learning and adaptive filters Adaptive signal processing / Mathematics Machine learning / Mathematics Signal processing / Digital techniques / Mathematics Digital filters (Mathematics) |
| title | Online learning and adaptive filters |
| title_auth | Online learning and adaptive filters |
| title_exact_search | Online learning and adaptive filters |
| title_exact_search_txtP | Online learning and adaptive filters |
| title_full | Online learning and adaptive filters Paulo S.R. Diniz [and four others] |
| title_fullStr | Online learning and adaptive filters Paulo S.R. Diniz [and four others] |
| title_full_unstemmed | Online learning and adaptive filters Paulo S.R. Diniz [and four others] |
| title_short | Online learning and adaptive filters |
| title_sort | online learning and adaptive filters |
| topic | Adaptive signal processing / Mathematics Machine learning / Mathematics Signal processing / Digital techniques / Mathematics Digital filters (Mathematics) |
| topic_facet | Adaptive signal processing / Mathematics Machine learning / Mathematics Signal processing / Digital techniques / Mathematics Digital filters (Mathematics) |
| url | https://doi.org/10.1017/9781108896139 |
| work_keys_str_mv | AT dinizpaulosergioramirez onlinelearningandadaptivefilters |