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

PDF download

PayPerView

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.