Codes for Adversaries: Between Worst-Case and Average-Case Jamming - Couverture souple

Dey, Bikash Kumar; Jaggi, Sidharth; Langberg, Michael; Sarwate, Anand D.; Zhang, Yihan

Couverture souple

ISBN 10 : 1638284601 ISBN 13 : 9781638284604

Editeur : now publishers Inc, 2024

Synopsis

Over the last 70 years, information theory and coding have enabled communication technologies that have had an astounding impact on our lives. This is possible due to the match between encoding/decoding strategies and corresponding channel models. Traditional studies of channels have taken one of two extremes: Shannon-theoretic models are inherently average-case in which channel noise is governed by a memoryless stochastic process, whereas coding-theoretic (referred to as "Hamming") models take a worst-case, adversarial, view of the noise. However, for several existing and emerging communication systems, the Shannon/average-case view may be too optimistic, whereas the Hamming/worst-case view may be too pessimistic. This monograph takes up the challenge of studying adversarial channel models that lie between the Shannon and Hamming extremes.

Détails de l'édition

• Éditeur: now publishers Inc
• Date d'édition: 2024
• Langue: anglais
• ISBN 10: 1638284601
• ISBN 13: 9781638284604
• Reliure: Broché
• Nombre de pages: 306
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible