• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.91-103
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• 2015

This paper presents "The 3-User NOR switching channel based on interference decoding with receiver cooperation" in succession to "Jeju Jong Nang channel code I, II". The Jeju Jong Nang code is considered as one of the earliest human binary coded communication (HBCC) in the world with a definite "1" or "0" binary symbolic analysis of switching circuits. In this paper, we introduce a practical example of interference decoding with receiver cooperation based on the three user Jong Nang NOR switching channel. The proposed system models are the three user Jong Nang (TUJN) NOR logic switching on-off, three-user injective deterministic NOR switching channel and Gaussian interference channel (GIC) with receiver cooperation. Therefore, this model is well matched to Shannon binary symmetric and erasure channel capacity. We show the applications of three-user Gaussian interference decoding to obtain deterministic channels which means each receiver cooperation helps to adjacent others in order to increase degree of freedom. Thus, the optimal sum rate of interference mitigation through adjacent receiver cooperation achieves 7 bits.

• Communications of Mathematical Education
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• v.34 no.1
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• pp.1-15
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• 2020

Today's healthcare, intelligent robots, smart home systems, and car sharing are already innovating with cutting-edge information and communication technologies such as Artificial Intelligence (AI), the Internet of Things, the Internet of Intelligent Things, and Big data. It is deeply affecting our lives. In the factory, robots have been working for humans more than several decades (FA, OA), AI doctors are also working in hospitals (Dr. Watson), AI speakers (Giga Genie) and AI assistants (Siri, Bixby, Google Assistant) are working to improve Natural Language Process. Now, in order to understand AI, knowledge of mathematics becomes essential, not a choice. Thus, mathematicians have been given a role in explaining such mathematics that make these things possible behind AI. Therefore, the authors wrote a textbook 'Basic Mathematics for Artificial Intelligence' by arranging the mathematics concepts and tools needed to understand AI and machine learning in one or two semesters, and organized lectures for undergraduate and graduate students of various majors to explore careers in artificial intelligence. In this paper, we share our experience of conducting this class with the full contents in http://matrix.skku.ac.kr/math4ai/.