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Random processes for engineers / Bruce Hajek, University of Illinois.

By: Material type: TextTextPublisher: Cambridge, UK : Cambridge University Press, 2015Description: xiii, 414 pages : illustrations ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 1107100127
  • 9781107100121
Subject(s): Additional physical formats: Ebook version: No title; No titleDDC classification:
  • 519.23 23
LOC classification:
  • TA340 .H325 2015
Contents:
1. A selective review of basic probability -- 2. Convergence of a sequence of random variables -- 3. Random vectors and minimum mean squared error estimation -- 4. Random processes -- 5. Inference for Markov models -- 6. Dynamics for countable-state Markov models -- 7. Basic calculus of random processes -- 8. Random processes in linear systems and spectral analysis -- 9. Wiener filtering -- 10. Martingales -- 11. Appendix -- 12. Solutions to even numbered problems.
Summary: "This engaging introduction to random processes provides students with the critical tools needed to design and evaluate engineering systems that must operate reliably in uncertain environments. A brief review of probability theory and real analysis of deterministic functions sets the stage for understanding random processes, whilst the underlying measure theoretic notions are explained in an intuitive, straightforward style. Students will learn to manage the complexity of randomness through the use of simple classes of random processes, statistical means and correlations, asymptotic analysis, sampling, and effective algorithms"--Publisher's website.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Book City Campus City Campus Main Collection 519.23 HAJ (Browse shelf(Opens below)) 1 Available A547081B

Includes bibliographical references and index.

1. A selective review of basic probability -- 2. Convergence of a sequence of random variables -- 3. Random vectors and minimum mean squared error estimation -- 4. Random processes -- 5. Inference for Markov models -- 6. Dynamics for countable-state Markov models -- 7. Basic calculus of random processes -- 8. Random processes in linear systems and spectral analysis -- 9. Wiener filtering -- 10. Martingales -- 11. Appendix -- 12. Solutions to even numbered problems.

"This engaging introduction to random processes provides students with the critical tools needed to design and evaluate engineering systems that must operate reliably in uncertain environments. A brief review of probability theory and real analysis of deterministic functions sets the stage for understanding random processes, whilst the underlying measure theoretic notions are explained in an intuitive, straightforward style. Students will learn to manage the complexity of randomness through the use of simple classes of random processes, statistical means and correlations, asymptotic analysis, sampling, and effective algorithms"--Publisher's website.

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