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• LDR

  03065nam a2200301 c 4500

• 001

  000000601214

• 005

  20150716105004

• 008

  150626s2012 us a b 001 eng

• 020

  ▼a  9780470609699(hardback)

• 020

  ▼a  0470609699 (hardback)

• 049

  ▼l  EM0000239507

• 082

  ▼a  621.3822
  ▼2  22

• 090

  ▼a  621.3822
  ▼b  B881i4

• 100

  ▼a  Brown, Robert Grover.

• 245

  ▼a  Introduction to random signals and applied Kalman filtering:
  ▼b  with MATLAB exercises/
  ▼d  Robert Grover Brown, Patrick Y.C. Hwang.

• 250

  ▼a  4th ed.

• 260

  ▼a  Hoboken, NJ:
  ▼b  John Wiley,
  ▼c  c2012.

• 300

  ▼a  xii, 383 p.:
  ▼b  ill.;
  ▼c  26 cm.

• 500

  ▼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

• 504

  ▼a  Includes bibliographical references and index

• 505

  ▼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

• 630

  ▼a  MATLAB

• 650

  ▼a  Signal processing
  ▼x  Data processing

• 650

  ▼a  Random noise theory

• 650

  ▼a  Kalman filtering
  ▼x  Data processing

• 700

  ▼a  Hwang, Patrick Y. C,

• 950

  ▼b  \42000

• 991

  ▼a  단행본

• 090

  ▼a  621.3822
  ▼b  B881i4