國立虎尾科技大學 |

Kalman Filtering and Information Fusion

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Kalman Filtering and Information Fusion/ by Hongbin Ma, Liping Yan, Yuanqing Xia, Mengyin Fu.
作者:	Ma, Hongbin.
其他作者:	Yan, Liping.
面頁冊數:	XVII, 291 p. 101 illus., 38 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Control engineering. -
電子資源:	https://doi.org/10.1007/978-981-15-0806-6
ISBN:	9789811508066

Kalman Filtering and Information Fusion
Ma, Hongbin.

Kalman Filtering and Information Fusion[electronic resource] /by Hongbin Ma, Liping Yan, Yuanqing Xia, Mengyin Fu. - 1st ed. 2020. - XVII, 291 p. 101 illus., 38 illus. in color.online resource.

Preface -- Part I Kalman Filtering: Preliminaries -- Part II Kalman Filtering for Uncertain Systems -- Part III Kalman Filtering for Multi-Sensor Systems -- Part IV Kalman Filtering for Multi-Agent Systems.

This book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the greatest discoveries of the 20th century. It introduces readers to issues concerning various uncertainties in a single plant, and to corresponding solutions based on adaptive estimation. Further, it discusses in detail the issues that arise when Kalman filtering technology is applied in multi-sensor systems and/or multi-agent systems, especially when various sensors are used in systems like intelligent robots, autonomous cars, smart homes, smart buildings, etc., requiring multi-sensor information fusion techniques. Furthermore, when multiple agents (subsystems) interact with one another, it produces coupling uncertainties, a challenging issue that is addressed here with the aid of novel decentralized adaptive filtering techniques. Overall, the book’s goal is to provide readers with a comprehensive investigation into the challenging problem of making Kalman filtering work well in the presence of various uncertainties and/or for multiple sensors/components. State-of-art techniques are introduced, together with a wealth of novel findings. As such, it can be a good reference book for researchers whose work involves filtering and applications; yet it can also serve as a postgraduate textbook for students in mathematics, engineering, automation, and related fields. To read this book, only a basic grasp of linear algebra and probability theory is needed, though experience with least squares, navigation, robotics, etc. would definitely be a plus.

ISBN: 9789811508066

Standard No.: 10.1007/978-981-15-0806-6doiSubjects--Topical Terms:

1249728
Control engineering.

LC Class. No.: TJ210.2-211.495

Dewey Class. No.: 629.8

Kalman Filtering and Information Fusion
LDR:03264nam a22004215i 4500 001 1026233
003 DE-He213
005 20200702005810.0
007 cr nn 008mamaa
008 210318s2020 si | s |||| 0|eng d
020 $a 9789811508066 $9 978-981-15-0806-6
024 7 $a 10.1007/978-981-15-0806-6 $2 doi
035 $a 978-981-15-0806-6
050 4 $a TJ210.2-211.495
050 4 $a TJ163.12
072 7 $a TJFM $2 bicssc
072 7 $a TEC004000 $2 bisacsh
072 7 $a TJFM $2 thema
072 7 $a TJFD $2 thema
082 0 4 $a 629.8 $2 23
100 1 $a Ma, Hongbin. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1108805
245 1 0 $a Kalman Filtering and Information Fusion $h [electronic resource] / $c by Hongbin Ma, Liping Yan, Yuanqing Xia, Mengyin Fu.
250 $a 1st ed. 2020.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a XVII, 291 p. 101 illus., 38 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Preface -- Part I Kalman Filtering: Preliminaries -- Part II Kalman Filtering for Uncertain Systems -- Part III Kalman Filtering for Multi-Sensor Systems -- Part IV Kalman Filtering for Multi-Agent Systems.
520 $a This book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the greatest discoveries of the 20th century. It introduces readers to issues concerning various uncertainties in a single plant, and to corresponding solutions based on adaptive estimation. Further, it discusses in detail the issues that arise when Kalman filtering technology is applied in multi-sensor systems and/or multi-agent systems, especially when various sensors are used in systems like intelligent robots, autonomous cars, smart homes, smart buildings, etc., requiring multi-sensor information fusion techniques. Furthermore, when multiple agents (subsystems) interact with one another, it produces coupling uncertainties, a challenging issue that is addressed here with the aid of novel decentralized adaptive filtering techniques. Overall, the book’s goal is to provide readers with a comprehensive investigation into the challenging problem of making Kalman filtering work well in the presence of various uncertainties and/or for multiple sensors/components. State-of-art techniques are introduced, together with a wealth of novel findings. As such, it can be a good reference book for researchers whose work involves filtering and applications; yet it can also serve as a postgraduate textbook for students in mathematics, engineering, automation, and related fields. To read this book, only a basic grasp of linear algebra and probability theory is needed, though experience with least squares, navigation, robotics, etc. would definitely be a plus.
650 0 $a Control engineering. $3 1249728
650 0 $a Robotics. $3 561941
650 0 $a Mechatronics. $3 559133
650 0 $a Applied mathematics. $3 1069907
650 0 $a Engineering mathematics. $3 562757
650 0 $a System theory. $3 566168
650 0 $a Electrical engineering. $3 596380
650 1 4 $a Control, Robotics, Mechatronics. $3 768396
650 2 4 $a Mathematical and Computational Engineering. $3 1139415
650 2 4 $a Systems Theory, Control. $3 669337
650 2 4 $a Electrical Engineering. $3 768742
700 1 $a Yan, Liping. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1322526
700 1 $a Xia, Yuanqing. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 785328
700 1 $a Fu, Mengyin. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 785329
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811508059
776 0 8 $i Printed edition: $z 9789811508073
776 0 8 $i Printed edition: $z 9789811508080
856 4 0 $u https://doi.org/10.1007/978-981-15-0806-6
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)