Paper Info
Title
Hierarchical Change-Detection Tests.
Abstract
We present hierarchical change-detection tests (HCDTs), as effective online algorithms for detecting changes in datastreams. HCDTs are characterized by a hierarchical architecture composed of a detection layer and a validation layer. The detection layer steadily analyzes the input datastream by means of an online, sequential CDT, which operates as a low-complexity trigger that promptly detects pos...
Year
DOI
Venue
2017
10.1109/TNNLS.2015.2512714
IEEE Transactions on Neural Networks and Learning Systems
Keywords
DocType
Volume
Monitoring,Change detection algorithms,Computer architecture,Algorithm design and analysis,Delays,Learning systems,Big data
Journal
28
Issue
ISSN
Citations 
2
2162-237X
18
PageRank 
References 
Authors
0.66
18
3
Name
Order
Citations
PageRank
Cesare Alippi11040115.84
Giacomo Boracchi232430.49
Manuel Roveri327230.19