On the finiteness of the capacity of continuous channels
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Institute of Electrical and Electronics Engineers Inc.
Abstract
Evaluating the channel capacity is one of many key problems in information theory. In this work, we derive rathermild sufficient conditions under which the capacity of continuous channels is finite and achievable. These conditions are derived for generic, memoryless, and possibly nonlinear additive noise channels. The results are based on a novel sufficient condition that guarantees the convergence of differential entropies under point-wise convergence of probability density functions. Perhaps surprisingly, the finiteness of channel capacity holds for the majority of setups, including those where inputs and outputs have possibly infinite second-moments. © 2015 IEEE.
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Keywords
Average cost constraints, Channel capacity, Convergence in differential entropy, Convex optimization, Infinite second moment, Super-logarithmic costs, Additive noise, Entropy, Information theory, Average cost, Differential entropy, Memoryless, Point wise, Second moments, Probability density function