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Introduction to random signals and applied Kalman filtering : with MATLAB exercises /

"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 Kal...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Brown, Robert Grover
Otros Autores: Hwang, Patrick Y. C.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, NJ : J. Wiley & Sons, ©2012.
Edición:4th ed.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Brown, Robert Grover. 
245 1 0 |a Introduction to random signals and applied Kalman filtering :  |b with MATLAB exercises /  |c Robert Grover Brown, Patrick Y.C. Hwang. 
250 |a 4th ed. 
260 |a Hoboken, NJ :  |b J. Wiley & Sons,  |c ©2012. 
300 |a 1 online resource (1 volume) :  |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. 
504 |a Includes bibliographical references and index. 
505 8 |a Machine 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. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
630 0 0 |a MATLAB. 
630 0 7 |a MATLAB.  |2 blmlsh 
630 0 7 |a MATLAB.  |2 fast  |0 (OCoLC)fst01365096 
650 0 |a Signal processing  |x Data processing. 
650 0 |a Random noise theory. 
650 0 |a Kalman filtering  |x Data processing. 
650 6 |a Traitement du signal  |x Informatique. 
650 6 |a Théorie du bruit aléatoire. 
650 6 |a Filtre de Kalman  |x Informatique. 
650 7 |a Kalman filtering  |x Data processing.  |2 fast  |0 (OCoLC)fst00985840 
650 7 |a Random noise theory.  |2 fast  |0 (OCoLC)fst01089805 
650 7 |a Signal processing  |x Data processing.  |2 fast  |0 (OCoLC)fst01118284 
700 1 |a Hwang, Patrick Y. C. 
776 0 8 |i Print version:  |a Brown, Robert Grover.  |t Introduction to random signals and applied Kalman filtering.  |b 4th ed.  |d Hoboken, NJ : John Wiley, ©2012  |z 9780470609699  |w (DLC) 2011042847  |w (OCoLC)711044717 
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