Kalman Filtering

with Real-Time Applications

AvCharles K. Chui,Guanrong Chen

Inbunden, Engelska, 2017

753 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Fler format och utgåvor

Häftad

540 kr

Häftad

656 kr

Beskrivning

Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals.

Produktinformation

Utgivningsdatum:2017-03-29
Mått:155 x 235 x 22 mm
Vikt:560 g
Format:Inbunden
Språk:Engelska
Antal sidor:247
Upplaga:5
Förlag:Springer International Publishing AG
ISBN:9783319476100

Utforska kategorier

Mer om författaren

Prof. Dr. Charles K. Chui, Stanford University, Stanford, CA, USA Prof. Dr. Guanrong Chen, City Univesity Hong Kong, Kowloon, Hong Kong, PR China

Recensioner i media

“This book is suitable for self-study as well as for use in a one-quarter or one-semester introductory course on Kalman filtering theory for upper-division undergraduate or first-year graduate to applied mathematics or engineering students.” (Mikhail P. Moklyachuk, zbMath 1416.93001, 2019)“Kalman filtering (KF) is a wide class of algorithms designed, in words selected from this outstanding book, ‘to obtain an optimal estimate’ of the state of a system from information in the presence of noise. … It is also written to serve as a reference for engineers … . The book has my highest recommendation, and it will reward readers for careful and iterative study of its text and well-designed exercises.” (Computing Reviews, October, 2017)

Innehållsförteckning

Preliminaries.- Kalman Filter: An Elementary Approach.- Orthogonal Projection and Kalman Filter.- Correlated System and Measurement Noise Processes.- Colored Noise.- Limiting Kalman Filter.- Sequential and Square-Root Algorithms.- Extended Kalman Filter and System Identification.- Decoupling of Filtering Equations.- Kalman Filtering for Interval Systems.- Wavelet Kalman Filtering.- Distributed Estimation on Sensor Networks.- Notes.- Answers and Hints to Exercises.