Dynamic Threshold Detection Using Clustering in the Presence of Channel Mismatch and Additive Noise

Dynamic Threshold Detection Using Clustering in the Presence of Channel Mismatch and Additive Noise

We report on the feasibility of k-means clustering techniques for the dynamic threshold detection of encoded q-ary symbols transmitted over a noisy channel with partially unknown channel parameters. We first assess the performance of k-means clustering technique without dedicated constrained coding....

Full description

Bibliographic Details
Main Authors: Kees A. Immink, Kui Cai
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Data storage systems
non-volatile memories
channel mismatch
<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k</italic>-means clustering
dynamic threshold detection
Online Access:https://ieeexplore.ieee.org/document/8967093/

Internet

https://ieeexplore.ieee.org/document/8967093/

Similar Items