Title :
Squeezing the Arimoto–Blahut Algorithm for Faster Convergence
Author_Institution :
Dept. of Stat., Univ. of California, Irvine, CA, USA
fDate :
7/1/2010 12:00:00 AM
Abstract :
The Arimoto-Blahut algorithm for computing the capacity of a discrete memoryless channel is revisited. A so-called “squeezing” strategy is used to design algorithms that preserve its simplicity and monotonic convergence properties, but have provably better rates of convergence.
Keywords :
channel capacity; convergence; Arimoto-Blahut algorithm; discrete memoryless channel capacity; monotonic convergence properties; squeezing strategy; Acceleration; Algorithm design and analysis; Channel capacity; Conferences; Convergence; Helium; Information theory; Iterative algorithms; Memoryless systems; Statistics; Alternating minimization; channel capacity; discrete memoryless channel; rate of convergence;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2010.2048452
