Introduction and implementations of the kalman filter / / edited by Felix Govaers.
Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localiz...
Saved in:
| : | |
|---|---|
| TeilnehmendeR: | |
| Place / Publishing House: | London, England : : IntechOpen,, [2019] ©2019 |
| Year of Publication: | 2019 |
| Language: | English |
| Physical Description: | 1 online resource (128 pages) :; illustrations |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
993546453004498 |
|---|---|
| ctrlnum |
(CKB)4100000008408625 (NjHacI)994100000008408625 (oapen)https://directory.doabooks.org/handle/20.500.12854/50595 (EXLCZ)994100000008408625 |
| collection |
bib_alma |
| record_format |
marc |
| spelling |
Felix Govaers auth Introduction and implementations of the kalman filter / edited by Felix Govaers. IntechOpen 2019 London, England : IntechOpen, [2019] ©2019 1 online resource (128 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Description based on: online resource; title from PDF information screen (InTech, viewed October 15, 2022). Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some ""awareness"" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not. English Kalman filtering. Physical Sciences Engineering and Technology Computer and Information Science Numerical Analysis and Scientific Computing Signal Processing 1-83880-536-2 Govaers, Felix, editor. |
| language |
English |
| format |
eBook |
| author |
Felix Govaers |
| spellingShingle |
Felix Govaers Introduction and implementations of the kalman filter / |
| author_facet |
Felix Govaers Govaers, Felix, |
| author_variant |
f g fg |
| author2 |
Govaers, Felix, |
| author2_variant |
f g fg |
| author2_role |
TeilnehmendeR |
| author_sort |
Felix Govaers |
| title |
Introduction and implementations of the kalman filter / |
| title_full |
Introduction and implementations of the kalman filter / edited by Felix Govaers. |
| title_fullStr |
Introduction and implementations of the kalman filter / edited by Felix Govaers. |
| title_full_unstemmed |
Introduction and implementations of the kalman filter / edited by Felix Govaers. |
| title_auth |
Introduction and implementations of the kalman filter / |
| title_new |
Introduction and implementations of the kalman filter / |
| title_sort |
introduction and implementations of the kalman filter / |
| publisher |
IntechOpen IntechOpen, |
| publishDate |
2019 |
| physical |
1 online resource (128 pages) : illustrations |
| isbn |
1-83880-739-X 1-83880-537-0 1-83880-536-2 |
| callnumber-first |
Q - Science |
| callnumber-subject |
QA - Mathematics |
| callnumber-label |
QA402 |
| callnumber-sort |
QA 3402.3 I587 42019 |
| illustrated |
Illustrated |
| dewey-hundreds |
600 - Technology |
| dewey-tens |
620 - Engineering |
| dewey-ones |
629 - Other branches of engineering |
| dewey-full |
629.8312 |
| dewey-sort |
3629.8312 |
| dewey-raw |
629.8312 |
| dewey-search |
629.8312 |
| work_keys_str_mv |
AT felixgovaers introductionandimplementationsofthekalmanfilter AT govaersfelix introductionandimplementationsofthekalmanfilter |
| status_str |
n |
| ids_txt_mv |
(CKB)4100000008408625 (NjHacI)994100000008408625 (oapen)https://directory.doabooks.org/handle/20.500.12854/50595 (EXLCZ)994100000008408625 |
| carrierType_str_mv |
cr |
| is_hierarchy_title |
Introduction and implementations of the kalman filter / |
| author2_original_writing_str_mv |
noLinkedField |
| _version_ |
1796651409912889344 |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01012nam a2200301 i 4500</leader><controlfield tag="001">993546453004498</controlfield><controlfield tag="005">20221015123358.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr |||||||||||</controlfield><controlfield tag="008">221015s2019 enka o 000 0 eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1-83880-739-X</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1-83880-537-0</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)4100000008408625</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(NjHacI)994100000008408625</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/50595</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)994100000008408625</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">NjHacI</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="c">NjHacl</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA402.3</subfield><subfield code="b">.I587 2019</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">629.8312</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Felix Govaers</subfield><subfield code="4">auth</subfield></datafield><datafield tag="245" ind1="0" ind2="0"><subfield code="a">Introduction and implementations of the kalman filter /</subfield><subfield code="c">edited by Felix Govaers.</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="b">IntechOpen</subfield><subfield code="c">2019</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">London, England :</subfield><subfield code="b">IntechOpen,</subfield><subfield code="c">[2019]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2019</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (128 pages) :</subfield><subfield code="b">illustrations</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on: online resource; title from PDF information screen (InTech, viewed October 15, 2022).</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some ""awareness"" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Kalman filtering.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Physical Sciences</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Engineering and Technology</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Computer and Information Science</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Numerical Analysis and Scientific Computing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Signal Processing</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">1-83880-536-2</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Govaers, Felix,</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2023-02-22 19:54:54 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2019-06-21 19:11:02 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5351663040004498&Force_direct=true</subfield><subfield code="Z">5351663040004498</subfield><subfield code="b">Available</subfield><subfield code="8">5351663040004498</subfield></datafield></record></collection> |