Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Chebyshev Center Computation on Probability Simplex With alpha-Divergence Measure
Date
2020-01-01
Author
Candan, Çağatay
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
4
views
0
downloads
Chebyshev center computation problem, i.e. finding the point which is at minimum distance to a set of given points, on the probability simplex with alpha-divergence distancemeasure is studied. The proposed solution generalizes the ArimotoBlahut (AB) algorithm utilizing Kullback-Leibler divergence to alpha-divergence, and reduces to the AB method as a. 1. Similar to the AB algorithm, themethod is an ascent method with a guarantee onthe objective value (alpha-mutual information or Chebyshev radius) improvement at every iteration. A practical application area for the method is the fusion of probability mass functions lacking a joint probability description. Another application area is the error exponent calculation.
Subject Keywords
Signal Processing
,
Electrical and Electronic Engineering
,
Applied Mathematics
URI
https://hdl.handle.net/11511/37796
Journal
IEEE SIGNAL PROCESSING LETTERS
DOI
https://doi.org/10.1109/lsp.2020.3018661
Collections
Department of Electrical and Electronics Engineering, Article