Signals, Systems and Inference, Global Edition, 1st edition

Published by Pearson (October 18, 2018) © 2019

  • Alan V Oppenheim
  • George C. Verghese Massachusetts Institute of Technology
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Details

  • A print copy
  • Free shipping

Features

  • Further reading sections
  • Basic, advanced and extension problems
  • Can be used for a 13-week course

This product is expected to ship within 10-12 business days for New Zealand customers.

For upper-level undergraduate courses in deterministic and stochastic signals and system engineering


An Integrative Approach to Signals, Systems and Inference

Signals, Systems and Inference is a comprehensive text that builds on introductory courses in time- and frequency-domain analysis of signals and systems, and in probability. Directed primarily to upper-level undergraduates and beginning graduate students in engineering and applied science branches, this new textbook pioneers a novel course of study. Instead of the usual leap from broad introductory subjects to highly specialised advanced subjects, this engaging and inclusive text creates a study track for a transitional course. 


Properties and representations of deterministic signals and systems are reviewed and elaborated on, including group delay and the structure and behavior of state-space models. The text also introduces and interprets correlation functions and power spectral densities for describing and processing random signals. Application contexts include pulse amplitude modulation, observer-based feedback control, optimum linear filters for minimum mean-square-error estimation, and matched filtering for signal detection. Model-based approaches to inference are emphasised, in particular for state estimation, signal estimation, and signal detection. 

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  • 1. Signals and Systems
  • 2. Amplitude, Phase, and Group Delay
  • 3. Pulse-Amplitude Modulation
  • 4. State-Space Models
  • 5. LTI State-Space Models
  • 6. State Observers and State Feedback
  • 7. Probabilistic Models
  • 8. Estimation
  • 9. Hypothesis Testing
  • 10. Random Processes
  • 11. Power Spectral Density
  • 12. Signal Estimation
  • 13. Signal Detection
  • Bibliography
  • Index

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