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Document type:
Bachelorarbeit 
Author(s):
Amine M'Charrak 
Title:
Clustering Algorithms for Lossy Data Compression 
Translated title:
Clustering Algorithms for Lossy Data Compression 
Abstract:
In this work, we compare different clustering algorithm implementations and optimize them with regards to their distortion behavior. The preferred clustering method for lossy data compression depends on the scenario or application we want to apply it to. After implementing the K-means algorithm and optimizing it towards the excess distortion performance criterion for a binary memoryless channel, we compare our found results with the achievability and converse results from related literature. We...    »
 
Translated abstract:
In this work, we compare different clustering algorithm implementations and optimize them with regards to their distortion behavior. The preferred clustering method for lossy data compression depends on the scenario or application we want to apply it to. After implementing the K-means algorithm and optimizing it towards the excess distortion performance criterion for a binary memoryless channel, we compare our found results with the achievability and converse results from related literature. We...    »
 
Subject:
DAT Datenverarbeitung, Informatik 
DDC:
000 Informatik, Wissen, Systeme 
Advisor:
Palzer, Lars 
Referee:
Kramer, Gerhard (Prof. Dr.) 
Year:
2016 
Pages:
82 
Language:
en 
Language from translation:
en 
University:
Technische Universität München 
Faculty:
Fakultät für Elektrotechnik und Informationstechnik