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Strong Converse, Feedback Channel Capacity and Hypothesis Testing \Lambda

Summary: Strong Converse, Feedback Channel Capacity
and Hypothesis Testing \Lambda
Po­Ning Chen Fady Alajaji
Computer & Communication Research Laboratories Department of Mathematics & Statistics
Industrial Technology Research Institute Queen's University
Taiwan 310, Republic of China Kingston, ON K7L 3N6, Canada
Journal of the Chinese Institute of Engineers, to appear November 1995
In light of recent results by Verd'u and Han on channel capacity, we examine three problems:
the strong converse condition to the channel coding theorem, the capacity of arbitrary channels
with feedback and the Neyman­Pearson hypothesis testing type­II error exponent. It is first
remarked that the strong converse condition holds if and only if the sequence of normalized channel
information densities converges in probability to a constant. Examples illustrating this condition
are also provided. A general formula for the capacity of arbitrary channels with output feedback
is then obtained. Finally, a general expression for the Neyman­Pearson type­II error exponent
based on arbitrary observations subject to a constant bound on the type­I error probability is
Key Words: Strong converse, channel capacity, channels with feedback, hypothesis testing.
\Lambda Parts of this paper were presented at the 1995 Conference on Information Sciences and Systems, The John
Hopkins University, Baltimore, MD, USA, March 1995.


Source: Alajaji, Fady - Department of Mathematics and Statistics, Queen's University (Kingston)


Collections: Engineering