Summary
The 2018 International Symposium on Information Theory and Its Applications　(ISITA2018)
2018
Session Number:Mo-PM-1-3
Session:
Number:Mo-PM-1-3.1
Detection of Noisy and Corrupted Data Using Clustering Techniques
Kui Cai, Kees Schouhamer Immink,
pp.135-138
Publication Date:2018/10/18
Online ISSN:2188-5079
DOI:10.34385/proc.55.Mo-PM-1-3.1
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Summary:
We investigate machine learning based on clustering techniques that are suitable for the detection of n-symbol words of q-ary symbols transmitted over a noisy channel with partially unknown characteristics. We consider the detection of the n- symbol q-ary data as a classification problem, where objects are recognized from a corrupted vector, which is obtained by an unknown corruption process.