Filtering and system identification: a least squares approach
Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Weitere beteiligte Personen: | |
| Format: | E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2007
|
| Links: | https://doi.org/10.1017/CBO9780511618888 |
| Zusammenfassung: | Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127. |
| Umfang: | 1 Online-Ressource (xv, 405 Seiten) |
| ISBN: | 9780511618888 |
Internformat
MARC
| LEADER | 00000nam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-20-CTM-CR9780511618888 | ||
| 003 | UkCbUP | ||
| 005 | 20151005020622.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 090915s2007||||enk o ||1 0|eng|d | ||
| 020 | |a 9780511618888 | ||
| 100 | 1 | |a Verhaegen, M. | |
| 245 | 1 | 0 | |a Filtering and system identification |b a least squares approach |c Michel Verhaegen, Vincent Verdult |
| 246 | 3 | |a Filtering & System Identification | |
| 264 | 1 | |a Cambridge |b Cambridge University Press |c 2007 | |
| 300 | |a 1 Online-Ressource (xv, 405 Seiten) | ||
| 336 | |b txt | ||
| 337 | |b c | ||
| 338 | |b cr | ||
| 520 | |a Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127. | ||
| 700 | 1 | |a Verdult, Vincent | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9780521875127 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781107405028 |
| 966 | 4 | 0 | |l DE-91 |p ZDB-20-CTM |q TUM_PDA_CTM |u https://doi.org/10.1017/CBO9780511618888 |3 Volltext |
| 912 | |a ZDB-20-CTM | ||
| 912 | |a ZDB-20-CTM | ||
| 049 | |a DE-91 | ||
Datensatz im Suchindex
| DE-BY-TUM_katkey | ZDB-20-CTM-CR9780511618888 |
|---|---|
| _version_ | 1825574053386125312 |
| adam_text | |
| any_adam_object | |
| author | Verhaegen, M. |
| author2 | Verdult, Vincent |
| author2_role | |
| author2_variant | v v vv |
| author_facet | Verhaegen, M. Verdult, Vincent |
| author_role | |
| author_sort | Verhaegen, M. |
| author_variant | m v mv |
| building | Verbundindex |
| bvnumber | localTUM |
| collection | ZDB-20-CTM |
| format | eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01962nam a2200277 i 4500</leader><controlfield tag="001">ZDB-20-CTM-CR9780511618888</controlfield><controlfield tag="003">UkCbUP</controlfield><controlfield tag="005">20151005020622.0</controlfield><controlfield tag="006">m|||||o||d||||||||</controlfield><controlfield tag="007">cr||||||||||||</controlfield><controlfield tag="008">090915s2007||||enk o ||1 0|eng|d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780511618888</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Verhaegen, M.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Filtering and system identification</subfield><subfield code="b">a least squares approach</subfield><subfield code="c">Michel Verhaegen, Vincent Verdult</subfield></datafield><datafield tag="246" ind1="3" ind2=" "><subfield code="a">Filtering & System Identification</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge</subfield><subfield code="b">Cambridge University Press</subfield><subfield code="c">2007</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xv, 405 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Verdult, Vincent</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">9780521875127</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">9781107405028</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-91</subfield><subfield code="p">ZDB-20-CTM</subfield><subfield code="q">TUM_PDA_CTM</subfield><subfield code="u">https://doi.org/10.1017/CBO9780511618888</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-20-CTM</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-20-CTM</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
| id | ZDB-20-CTM-CR9780511618888 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-03T11:58:07Z |
| institution | BVB |
| isbn | 9780511618888 |
| language | English |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource (xv, 405 Seiten) |
| psigel | ZDB-20-CTM TUM_PDA_CTM ZDB-20-CTM |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Cambridge University Press |
| record_format | marc |
| spelling | Verhaegen, M. Filtering and system identification a least squares approach Michel Verhaegen, Vincent Verdult Filtering & System Identification Cambridge Cambridge University Press 2007 1 Online-Ressource (xv, 405 Seiten) txt c cr Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127. Verdult, Vincent Erscheint auch als Druck-Ausgabe 9780521875127 Erscheint auch als Druck-Ausgabe 9781107405028 |
| spellingShingle | Verhaegen, M. Filtering and system identification a least squares approach |
| title | Filtering and system identification a least squares approach |
| title_alt | Filtering & System Identification |
| title_auth | Filtering and system identification a least squares approach |
| title_exact_search | Filtering and system identification a least squares approach |
| title_full | Filtering and system identification a least squares approach Michel Verhaegen, Vincent Verdult |
| title_fullStr | Filtering and system identification a least squares approach Michel Verhaegen, Vincent Verdult |
| title_full_unstemmed | Filtering and system identification a least squares approach Michel Verhaegen, Vincent Verdult |
| title_short | Filtering and system identification |
| title_sort | filtering and system identification a least squares approach |
| title_sub | a least squares approach |
| work_keys_str_mv | AT verhaegenm filteringandsystemidentificationaleastsquaresapproach AT verdultvincent filteringandsystemidentificationaleastsquaresapproach AT verhaegenm filteringsystemidentification AT verdultvincent filteringsystemidentification |