Potentials of Learning Entropy for Sub-Nyquist and Sub-Noise Anomaly Detection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F24%3A10133720" target="_blank" >RIV/63839172:_____/24:10133720 - isvavai.cz</a>
Alternative codes found
RIV/60076658:12310/24:43909518
Result on the web
<a href="https://ieeexplore.ieee.org/document/10805128" target="_blank" >https://ieeexplore.ieee.org/document/10805128</a>
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Potentials of Learning Entropy for Sub-Nyquist and Sub-Noise Anomaly Detection
Original language description
Recently, we have noted the intriguing ability of Learning Entropy (LE) with Higher-Order Neural Units (HONUs) to detect abrupt frequency changes in both sub-Nyquist signals and pure noise signals. The concept of the LE and its fundamental element, the Learning Information (LI), is revised and extended. The LI is presented as the logical counterpart of Shannon's probabilistic information and the LE as its aggregation, e.g. as an average. The approach emphasizes the computational efficiency and analyzability of HONUs with gradient learning, which implies minimal computational and energy requirements for real-time computations. For pure noise, we show that bandpass filtering and principal components improve LE performance to immediately detect frequency changes below the noise level. By demonstrating the ability of LE with linear units to detect anomalies in undersampled signals and also in pure noise, we show the potential of LE for industrial applications and perhaps also for research related to future digital communication systems or advanced analysis of data from distributed sensors in optical transmission infrastructures.
Czech name
—
Czech description
—

Project
<a href="/en/project/LM2023054" target="_blank" >LM2023054: e-Infrastructure CZ</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2024 SICE Festival with Annual Conference, SICE FES 2024
ISBN
978-4-907764-83-8
ISSN
—
e-ISSN
—
Number of pages
7
Pages from-to
584-590
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
NEW YORK, USA
Event location
Kochi City, Japonsko
Event date
Aug 27, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001424958800050

Similar results(10)