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Probability and Stochastic Processes : A Friendly Introduction for Electrical and Computer Engineers / by Roy D Yates and David J Goodman

By: Contributor(s): Material type: TextTextLanguage: English Publication details: New Delhi : Wiley , 2005 .Edition: 2ndDescription: xvii,519pISBN:
  • 9788126534319
Subject(s): Other classification:
  • B281 P5 TB
Summary: This user-friendly resource helps readers grasp the concepts of probability and stochastic processes, so they can apply them in professional engineering practice. The book presents concepts clearly as a sequence of building blocks that are identified either as an axiom, definition, or theorem. This approach provides a better understanding of the material, which can be used to solve practical problems. • Experiments, Models, and Probabilities. • Discrete Random Variables. • Continuous Random Variables. • Pairs of Random Variables. • Random Vectors. • Sums of Random Variables. • Parameter Estimation Using the Sample Mean. • Hypothesis Testing. • Estimation of a Random Variable. • Stochastic Processes. • Random Signal Processing. • Markov Chains.
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Item type Current library Home library Call number Status Barcode
Textbook Textbook Central Science Library Central Science Library B281 P5 TB (Browse shelf(Opens below)) Available SL1558514

Included Appendix A & B 501-510p.; References 511-512p.; Index 513-519p.

This user-friendly resource helps readers grasp the concepts of probability and stochastic processes, so they can apply them in professional engineering practice. The book presents concepts clearly as a sequence of building blocks that are identified either as an axiom, definition, or theorem. This approach provides a better understanding of the material, which can be used to solve practical problems. • Experiments, Models, and Probabilities. • Discrete Random Variables. • Continuous Random Variables. • Pairs of Random Variables. • Random Vectors. • Sums of Random Variables. • Parameter Estimation Using the Sample Mean. • Hypothesis Testing. • Estimation of a Random Variable. • Stochastic Processes. • Random Signal Processing. • Markov Chains.

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