000			03387cam a22003734a 4500
001			16998354
005			20191203140912.0
008			111013s2012 njua 001 0 eng
010			_a 2011042847
020			_a9780470609699 (hardback)
035			_a(OCoLC)ocn711044717
040			_aDLC _dYDX _dBTCTA _dYDXCP _dBWX _dBDX _dCDX _dSTF _dDLC
042			_apcc
050	0	0	_aTK5102.9 _b.B75 2012
082	0	0	_a621.382/2 _223
084			_aTEC007000 _2bisacsh
100	1		_aBrown, Robert Grover.
245	1	0	_aIntroduction to random signals and applied Kalman filtering : _bwith MATLAB exercises / _cRobert Grover Brown, Patrick Y.C. Hwang.
250			_a4th ed.
260			_aHoboken, NJ : _bJohn Wiley, _cc2012.
300			_axii, 383 p. : _bill. ; _c26 cm.
500			_aMachine generated contents note: PART 1: RANDOM SIGNALS BACKGROUND Chapter 1 Probability and Random Variables: A Review Chapter 2 Mathematical Description of Random Signals Chapter 3 Linear Systems Response, State-space Modeling and Monte Carlo Simulation PART 2: KALMAN FILTERING AND APPLICATIONS Chapter 4 Discrete Kalman Filter Basics Chapter 5 Intermediate Topics on Kalman Filtering Chapter 6 Smoothing and Further Intermediate Topics Chapter 7 Linearization, Nonlinear Filtering and Sampling Bayesian Filters Chapter 8 the "Go-Free" Concept, Complementary Filter and Aided Inertial Examples Chapter 9 Kalman Filter Applications to the GPS and Other Navigation Systems APPENDIX A. Laplace and Fourier Transforms APPENDIX B. The Continuous Kalman Filter.
504			_aIncludes bibliographical references and index.
505	8		_aMachine generated contents note: PART 1. RANDOM SIGNALS BACKGROUND Chapter 1 Probability and Random Variables: A Review Chapter 2. Mathematical Description of Random Signals Chapter 3. Linear Systems Response, State-Space Modeling, and Monte Carlo Simulation -- PART 2. KALMAN FILTERING AND APPLICATIONS Chapter 4. Discrete Kalman Filter Basics Chapter 5. Intermediate Topics on Kalman Filtering Chapter 6. Smoothing and Further Intermediate Topics Chapter 7. Linearization, Nonlinear Filtering, and Sampling Bayesian Filters Chapter 8. The "Go-Free" Concept, Complementary Filter, and Aided Inertial Examples Chapter 9. Kalman Filter Applications to the GPS and Other Navigation Systems APPENDIX A. Laplace and Fourier Transforms APPENDIX B. The Continuous Kalman Filter.
520			_a"The Fourth Edition to the Introduction of Random Signals and Applied Kalman Filtering is updated to cover innovations in the Kalman filter algorithm and the proliferation of Kalman filtering applications from the past decade. The text updates both the research advances in variations on the Kalman filter algorithm and adds a wide range of new application examples. Several chapters include a significant amount of new material on applications such as simultaneous localization and mapping for autonomous vehicles, inertial navigation systems and global satellite navigation systems"--Provided by publisher.
630	0	0	_aMATLAB.
650		0	_aSignal processing _xData processing.
650		0	_aRandom noise theory.
650		0	_aKalman filtering _xData processing.
700	1		_aHwang, Patrick Y. C.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2udc _cBK
999			_c28217 _d28217