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Bregman-divergence-based Arimoto-Blahut algorithm
- Publication Year :
- 2024
-
Abstract
- We generalize the generalized Arimoto-Blahut algorithm to a general function defined over Bregman-divergence system. In existing methods, when linear constraints are imposed, each iteration needs to solve a convex minimization. Exploiting our obtained algorithm, we propose a convex-optimization-free algorithm. This algorithm can be applied to classical and quantum rate-distortion theory. We numerically apply our method to the derivation of the optimal conditional distribution in the rate-distortion theory.
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2408.05454
- Document Type :
- Working Paper