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Communication Principles for Data Science

This book introduces the basic principles underlying the design and analysis of the digital communication systems that have heralded the information revolution. One major goal of the book is to demonstrate the role of the digital communication principles in a wide variety of data science application...

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Bibliografske podrobnosti
Glavni avtor: Suh, Changho (Author)
Korporativna značnica: SpringerLink (Online service)
Format: Elektronski eKnjiga
Jezik:angleščina
Izdano: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Izdaja:1st ed. 2023.
Serija:Signals and Communication Technology,
Teme:
Artificial intelligence > Data processing.
Digital media.
Computer science > Mathematics.
Mathematical statistics.
Signal processing.
Data Science.
Digital and New Media.
Probability and Statistics in Computer Science.
Signal, Speech and Image Processing.
Online dostop:https://doi.org/10.1007/978-981-19-8008-4
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Kazalo:
  • Preface
  • Acknowledgements
  • Part 1. Communication over the Gaussian channel
  • Chapter 1.Overview of the book
  • Chapter 2. A statistical model for additive noise channels
  • Chapter 3. Additive Gaussian noise model
  • Problem Set 1
  • Chapter 4. Optimal receiver: maximum A Posteriori (MAP) principle
  • Chapter 5. Analysis of error probability
  • Chapter 6. Multiple bits transmission via pulse amplitude modulation
  • Problem Set 2
  • Chapter 7. Multi-shot communication
  • Chapter 8. Repetition coding
  • Chapter 9: Capacity of the additive white Gaussian noise channel
  • Problem Set 3
  • Part 2. Communication over inter-symbol interference (ISI) channels
  • Chapter 10. Signal conversion from discrete to continuous time (1/2)
  • Chapter 11. Signal conversion from discrete to continuous time (2/2)
  • Chapter 12. Optimal receiver architecture
  • Problem Set 4
  • Chapter 13. Optimal receiver in ISI channels: maximum likelihood (ML) sequence detection
  • Chapter 14. Optimal receiver in ISI channels: Viterbi algorithm
  • Problem Set 5
  • Chapter 15.Orthogonal frequency division multiplexing (1/3)
  • Chapter 16. Orthogonal frequency division multiplexing (2/3)
  • Chapter 17. Orthogonal frequency division multiplexing (3/3)
  • Problem Set 6
  • Part 3.Data science applications
  • Chapter 18. Community detection as a communication problem
  • Chapter 19. Community detection: ML principle
  • Chapter 20. Community detection: An efficient algorithm
  • Chapter 21. Community detection: Python implementation
  • Problem Set 7
  • Chapter 22.Haplotype phasing as a communication problem
  • Chapter 23. Haplotype phasing: ML principle
  • Chapter 24: Haplotype phasing: An efficient algorithm. .

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