| Tag |
First Indicator |
Second Indicator |
Subfields |
| LEADER |
00000cam a2200000Ma 4500 |
| 001 |
in00005520719 |
| 006 |
m o d |
| 007 |
cr |n||||||||| |
| 008 |
170714s2017 enka o 000 0 eng d |
| 005 |
20241108165523.9 |
| 035 |
|
|
|a (OCoLC)ocn993696533
|
| 040 |
|
|
|a IDEBK
|b eng
|e pn
|c IDEBK
|d N$T
|d OCLCO
|d OCLCQ
|d CUS
|d OCLCQ
|d OCLCO
|d YDX
|d EBLCP
|d COO
|d UIU
|d CNCGM
|d VLB
|d ERL
|d UAB
|d OCLCQ
|d OCLCF
|d OCLCQ
|d UKMGB
|d OCLCQ
|d K6U
|d OCLCO
|d OCLCQ
|d OCLCO
|d OCLCL
|
| 015 |
|
|
|a GBB7E7872
|2 bnb
|
| 016 |
7 |
|
|a 018427819
|2 Uk
|
| 019 |
|
|
|a 993986802
|
| 020 |
|
|
|a 1498745180
|q (electronic bk.)
|
| 020 |
|
|
|a 9781498745185
|q (electronic bk.)
|
| 020 |
|
|
|a 9781351647953
|q (electronic bk.)
|
| 020 |
|
|
|a 1351647954
|q (electronic bk.)
|
| 020 |
|
|
|a 9781315151908
|q (electronic bk.)
|
| 020 |
|
|
|a 1315151901
|q (electronic bk.)
|
| 020 |
|
|
|z 1498745172
|
| 020 |
|
|
|z 9781498745178
|
| 035 |
|
|
|a (OCoLC)993696533
|z (OCoLC)993986802
|
| 037 |
|
|
|a 1021190
|b MIL
|
| 050 |
|
4 |
|a QA274
|
| 072 |
|
7 |
|a MAT
|x 003000
|2 bisacsh
|
| 072 |
|
7 |
|a MAT
|x 029000
|2 bisacsh
|
| 082 |
0 |
4 |
|a 519.2
|2 23
|
| 049 |
|
|
|a TXAM
|
| 100 |
1 |
|
|a Raol, Jitendra R.
|
| 245 |
1 |
0 |
|a Nonlinear Filtering.
|
| 260 |
|
|
|a London :
|b CRC Press,
|c 2017.
|
| 300 |
|
|
|a 1 online resource (556 pages) :
|b illustrations
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a computer
|b c
|2 rdamedia
|
| 338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
| 588 |
0 |
|
|a Print version record.
|
| 505 |
0 |
|
|a Cover; Half Title; Title; Copyright; Dedication; Contents; Preface; Acknowledgements; Authors; Introduction; Section I Mathematical Models, Kalman Filtering and H-Infinity Filters; Chapter 1. Dynamic System Models and Basic Concepts; 1.1 Dynamic Systems: The Need for Modelling, Parameter Estimation and Filtering; 1.2 Mathematical Modelling of Systems; 1.2.1 Time and Frequency Domain Aspects; 1.2.2 Differential Equations; 1.2.3 Difference Equations; 1.2.4 State Space Models; 1.2.4.1 Physical Representation; 1.2.4.2 Controllable Canonical Form; 1.2.4.3 Observable Canonical Form.
|
| 505 |
8 |
|
|a 1.2.4.4 Diagonal Form1.2.4.5 General State Space Models; 1.2.5 Polynomial Models; 1.2.6 Time Series Models; 1.2.6.1 Autoregressive Model; 1.2.6.2 Least Squares Model; 1.2.7 Transfer Function Models; 1.3 Nonlinear Dynamic Systems; 1.3.1 Nonlinearities in a System; 1.3.2 Mathematical Models of Nonlinear Systems; 1.3.2.1 Nonlinear Differential and Difference Equations; 1.3.2.2 Volterra Series; 1.3.2.3 Hammerstein Model; 1.3.2.4 Nonlinear State Space Models; 1.3.2.5 Nonlinear Time Series Models; 1.4 Signal and System Norms; 1.4.1 Signal Norms; 1.4.2 System Norms; 1.4.2.1 H2 Norm; 1.4.2.2 H∞ Norm
|
| 505 |
8 |
|
|a 1.5 Digital Signal Processing, Parameter Estimation and Filtering1.5.1 Signal Processing; 1.5.2 Parameter Estimation: Recursive Approach; 1.5.3 Filtering Concepts; 1.5.4 Simple Recursive Filtering; Appendix 1A: Mean Square Estimation; Appendix 1B: Nonlinear Models Based on Artificial Neural Networks and Fuzzy Logic; Appendix 1C: Illustrative Examples; Chapter 2. Filtering and Smoothing; 2.1 Wiener Filtering; 2.2 Least Squares Parameter Estimation; 2.3 Recursive Least Squares Filter; 2.4 State Space Models and Kalman Filtering; 2.4.1 Discrete Time Filter.
|
| 505 |
8 |
|
|a 2.4.1.1 State and Covariance Matrix Propagation2.4.1.2 Measurement Update; 2.4.1.3 Kalman Gain; 2.4.2 Continuous Time Kalman Filter; 2.4.3 Interpretation of Kalman Filter; 2.4.3.1 Continuous Time Filter; 2.4.3.2 Discrete Time Filter; 2.4.4 Filters for Correlated/Coloured Process and Measurement Noises; 2.4.4.1 Kalman Filter for the Correlated Process and Measurement Noises; 2.4.4.2 Handling of Coloured Process Noise and Coloured Measurement Noise in Kalman Filters; 2.4.5 Time-Varying Linear Kalman Filters; 2.4.6 Steady State Filtering; 2.4.7 Kalman Filter Implementation Aspects.
|
| 505 |
8 |
|
|a 2.4.8 Parallelization of Kalman Filters2.4.8.1 Measurement Update Parallelization; 2.4.8.2 Time Propagation Parallelization; 2.5 Filter Error Methods; 2.5.1 Output Error Method; 2.5.2 Process Noise Algorithms for Linear Systems; 2.5.2.1 Natural Formulation; 2.5.2.2 Innovations Formulation; 2.5.2.3 Mixed Formulation; 2.5.3 Process Noise Algorithms for Nonlinear Systems; 2.5.3.1 Steady-State Filter; 2.5.3.2 Time-Varying Filter; 2.6 Information Filtering; 2.6.1 Fisher's Information Concept; 2.6.2 Linear Information Filter; 2.7 Smoothers.
|
| 520 |
|
|
|a Nonlinear Filtering covers linear and nonlinear filtering in a comprehensive manner, with appropriate theoretic and practical development. Aspects of modeling, estimation, recursive filtering, linear filtering, and nonlinear filtering are presented with appropriate and sufficient mathematics. A modeling-control-system approach is used when applicable, and detailed practical applications are presented to elucidate the analysis and filtering concepts. MATLAB routines are included, and examples from a wide range of engineering applications - including aerospace, automated manufacturing, robotics, and advanced control systems - are referenced throughout the text.--Provided by publisher.
|
| 650 |
|
0 |
|a Stochastic processes.
|
| 650 |
|
0 |
|a Filters (Mathematics)
|
| 650 |
|
0 |
|a Nonlinear theory.
|
| 650 |
|
0 |
|a Engineering mathematics.
|
| 650 |
|
2 |
|a Stochastic Processes
|
| 650 |
|
6 |
|a Processus stochastiques.
|
| 650 |
|
6 |
|a Filtres (Mathématiques)
|
| 650 |
|
6 |
|a Mathématiques de l'ingénieur.
|
| 650 |
|
7 |
|a MATHEMATICS
|x Applied.
|2 bisacsh
|
| 650 |
|
7 |
|a MATHEMATICS
|x Probability & Statistics
|x General.
|2 bisacsh
|
| 650 |
|
7 |
|a Engineering mathematics
|2 fast
|
| 650 |
|
7 |
|a Filters (Mathematics)
|2 fast
|
| 650 |
|
7 |
|a Stochastic processes
|2 fast
|
| 655 |
|
7 |
|a Electronic books.
|2 local
|
| 710 |
2 |
|
|a Taylor & Francis.
|
| 758 |
|
|
|i has work:
|a Nonlinear filtering (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGDRdb3q8grDhF3MpbhY6C
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Raol, Jitendra R.
|t Nonlinear Filtering.
|d London : CRC Press, 2017
|z 9781498745178
|z 1498745172
|w (DLC) 2016050885
|w (OCoLC)967774858
|
| 856 |
4 |
0 |
|u http://proxy.library.tamu.edu/login?url=https://www.taylorfrancis.com/books/9781315151908
|z Connect to the full text of this electronic book
|t 0
|
| 955 |
|
|
|a Taylor and Francis ENGnetBASE
|
| 994 |
|
|
|a 92
|b TXA
|
| 999 |
f |
f |
|s eb3c42ee-df3e-4b6a-b5e0-0d6a8e793e1f
|i 467c1111-f487-489c-9605-ca08045787d0
|t 0
|
| 952 |
f |
f |
|a Texas A&M University
|b College Station
|c Electronic Resources
|d Available Online
|t 0
|e QA274
|h Library of Congress classification
|
| 998 |
f |
f |
|a QA274
|t 0
|l Available Online
|