Algorithmic Computability and Approximability of Capacity-Achieving Input Distributions-Reference-Cited by-同舟云学术

Algorithmic Computability and Approximability of Capacity-Achieving Input Distributions

Author:

Boche Holger¹^ORCID,Schaefer Rafael F.²^ORCID,Poor H. Vincent³^ORCID

Affiliation:

1. Institute of Theoretical Information Technology, Technical University of Munich, Munich, Germany

2. Chair of Information Theory and Machine Learning, Technical University of Dresden, Dresden, Germany

3. Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, USA

Funder

Bavarian Ministry of Economic Affairs, Regional Development and Energy as part of the Project 6G Future Lab Bavaria

German Federal Ministry of Education and Research (BMBF) within the National Initiative on 6G Communication Systems through the Research Hub 6G-Life

National Initiative on Post Shannon Communication

Project Hardware Platforms and Computing Models for Neuromorphic Computing

BMBF within NewCom

BMBF within 6G-Life

German Research Foundation

U.S. National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Library and Information Sciences,Computer Science Applications,Information Systems

Link

Reference47 articles.

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