Data Compression – Exploring New Techniques: Data Compression - An Intelligent Approach - Couverture souple

Chakraborty, Debashis; Bera, Sandipan; Ghosh, Sutirtha

 
9783659135767: Data Compression – Exploring New Techniques: Data Compression - An Intelligent Approach
Couverture souple
ISBN 10 : 3659135763 ISBN 13 : 9783659135767
Editeur : LAP LAMBERT Academic Publishing, 2012

Synopsis

Our project comprises of analysis of the existing algorithms for data compression so that we can utilize some features of these algorithms use them to build a more efficient algorithm. We have also considered detailed study to observe the efficiency of the algorithms for different document types with the intention of building a comprehensive data compression technique. We need to study and analyze all the algorithms separately to incorporate the positives from each of them and try to rectify the flaws that exist in these algorithms. For clear elucidation of the data compression concepts we try to discuss each standard algorithm in detail. There is a close connection between machine learning and compression: a system that predicts the posterior probabilities of a sequence given its entire history can be used for optimal data compression (by using arithmetic coding on the output distribution), while an optimal compressor can be used for prediction (by finding the symbol that compresses best, given the previous history). This equivalence has been used as justification for data compression as a benchmark for "general intelligence".

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Our project comprises of analysis of the existing algorithms for data compression so that we can utilize some features of these algorithms use them to build a more efficient algorithm. We have also considered detailed study to observe the efficiency of the algorithms for different document types with the intention of building a comprehensive data compression technique. We need to study and analyze all the algorithms separately to incorporate the positives from each of them and try to rectify the flaws that exist in these algorithms. For clear elucidation of the data compression concepts we try to discuss each standard algorithm in detail. There is a close connection between machine learning and compression: a system that predicts the posterior probabilities of a sequence given its entire history can be used for optimal data compression (by using arithmetic coding on the output distribution), while an optimal compressor can be used for prediction (by finding the symbol that compresses best, given the previous history). This equivalence has been used as justification for data compression as a benchmark for "general intelligence".

Biographie de l'auteur

Mr. Debashis Chakraborty is an Assistant Professor in the department of Computer Science and Engineering, st. Thomas’ College of Engineering and Technology, Kolkata, West Bengal, India. He has authored or co-authored over 10 conference and journal papers in area of Data and Image Compression.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2012
Langue
anglais
ISBN 10 
3659135763
ISBN 13 
9783659135767
Reliure
Broché
Nombre de pages
72
Coordonnées du fabricant
non disponible
Personne responsable
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