Fully updated for the second edition, this intuitive yet mathematically rigorous text derives the key results of digital communication from first principles. It includes new chapters on the radar problem and intersymbol interference channels, a more geometric derivation of optimal detection in white Gaussian noise, and over 500 homework problems.
Fully updated for the second edition, this intuitive yet mathematically rigorous text derives the key results of digital communication from first principles. It includes new chapters on the radar problem and intersymbol interference channels, a more geometric derivation of optimal detection in white Gaussian noise, and over 500 homework problems.
Amos Lapidoth is Professor of Information Theory at Eidgenössische Technische Hochschule Zürich, the Swiss Federal Institute of Technology, and a Fellow of the Institute of Electrical and Electronics Engineers. He received his PhD in Electrical Engineering from Stanford University, California and has held the positions of Assistant Professor and Associate Professor at the Massachusetts Institute of Technology.
Inhaltsangabe
1. Some essential notation 2. Signals, integrals, and sets of measure zero 3. The inner product 4. The space L2 of energy-limited signals 5. Convolutions and filters 6. The frequency response of filters and bandlimited signals 7. Passband signals and their representation 8. Complete orthonormal systems and the sampling theorem 9. Sampling real passband signals 10. Mapping bits to waveforms 11. Nyquist's criterion 12. Stochastic processes: definition 13. Stationary discrete-time stochastic processes 14. Energy and power in PAM 15. Operational power spectral density 16. Quadrature amplitude modulation 17. Complex random variables and processes 18. Energy, power, and PSD in QAM 19. The univariate Gaussian distribution 20. Binary hypothesis testing 21. Multi-hypothesis testing 22. Sufficient statistics 23. The multivariate Gaussian distribution 24. Complex Gaussians and circular symmetry 25. Continuous-time stochastic processes 26. Detection in white Gaussian noise 27. Noncoherent detection and nuisance parameters 28. Detecting PAM and QAM signals in white Gaussian noise 29. Linear binary block codes with antipodal signaling 30. The radar problem 31. A glimpse at discrete-time signal processing 32. Intersymbol interference.
1. Some essential notation 2. Signals, integrals, and sets of measure zero 3. The inner product 4. The space L2 of energy-limited signals 5. Convolutions and filters 6. The frequency response of filters and bandlimited signals 7. Passband signals and their representation 8. Complete orthonormal systems and the sampling theorem 9. Sampling real passband signals 10. Mapping bits to waveforms 11. Nyquist's criterion 12. Stochastic processes: definition 13. Stationary discrete-time stochastic processes 14. Energy and power in PAM 15. Operational power spectral density 16. Quadrature amplitude modulation 17. Complex random variables and processes 18. Energy, power, and PSD in QAM 19. The univariate Gaussian distribution 20. Binary hypothesis testing 21. Multi-hypothesis testing 22. Sufficient statistics 23. The multivariate Gaussian distribution 24. Complex Gaussians and circular symmetry 25. Continuous-time stochastic processes 26. Detection in white Gaussian noise 27. Noncoherent detection and nuisance parameters 28. Detecting PAM and QAM signals in white Gaussian noise 29. Linear binary block codes with antipodal signaling 30. The radar problem 31. A glimpse at discrete-time signal processing 32. Intersymbol interference.
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