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Extract from the Register of European Patents

EP About this file: EP4152210

EP4152210 - SYSTEM AND METHOD FOR TRAINING AN AUTOENCODER TO DETECT ANOMALOUS SYSTEM BEHAVIOUR [Right-click to bookmark this link]
StatusThe application has been published
Status updated on  17.02.2023
Database last updated on 19.10.2024
Most recent event   Tooltip07.11.2023New entry: Additional fee for renewal fee: despatch of communication + time limit 
Applicant(s)For all designated states
BAE SYSTEMS plc
6 Carlton Gardens
London SW1Y 5AD / GB
[2023/12]
Representative(s)BAE SYSTEMS plc Group IP Department
Warwick House
P.O. Box 87
Farnborough Aerospace Centre
Farnborough Hampshire GU14 6YU / GB
[2023/12]
Application number, filing date21275130.915.09.2021
[2023/12]
Filing languageEN
Procedural languageEN
PublicationType: A1 Application with search report 
No.:EP4152210
Date:22.03.2023
Language:EN
[2023/12]
Search report(s)(Supplementary) European search report - dispatched on:EP04.04.2022
ClassificationIPC:G06N3/04, G06N3/08, G06N5/00, G06N20/00
[2023/12]
CPC:
G06N3/088 (EP); G06F21/552 (EP); G06N3/042 (EP);
G06N3/0442 (EP); G06N3/0455 (EP); G06N3/0895 (EP);
G06N20/00 (EP); G06N5/01 (EP) (-)
Designated contracting statesAL,   AT,   BE,   BG,   CH,   CY,   CZ,   DE,   DK,   EE,   ES,   FI,   FR,   GB,   GR,   HR,   HU,   IE,   IS,   IT,   LI,   LT,   LU,   LV,   MC,   MK,   MT,   NL,   NO,   PL,   PT,   RO,   RS,   SE,   SI,   SK,   SM,   TR [2023/12]
Extension statesBANot yet paid
MENot yet paid
Validation statesKHNot yet paid
MANot yet paid
MDNot yet paid
TNNot yet paid
TitleGerman:SYSTEM UND VERFAHREN ZUM TRAINIEREN EINES AUTOCODIERERS ZUR ERKENNUNG VON ANOMALEM SYSTEMVERHALTEN[2023/12]
English:SYSTEM AND METHOD FOR TRAINING AN AUTOENCODER TO DETECT ANOMALOUS SYSTEM BEHAVIOUR[2023/12]
French:SYSTÈME ET PROCÉDÉ PERMETTANT D'ENTRAÎNER UN AUTO-ENCODEUR POUR DÉTECTER UN COMPORTEMENT ANORMAL D'UN SYSTÈME[2023/12]
Examination procedure29.03.2023Despatch of communication that the application is refused, reason: Examination on filing A.90(5) {1}
Fees paidPenalty fee
Additional fee for renewal fee
30.09.202303   M06   Not yet paid
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Documents cited:Search[A]  - ARELLANO-ESPITIA FRANCISCO ET AL, "Deep-Compact-Clustering Based Anomaly Detection Applied to Electromechanical Industrial Systems", SENSORS, vol. 21, no. 17, doi:10.3390/s21175830, (20210830), pages 1 - 25, URL: https://upcommons.upc.edu/bitstream/handle/2117/358140/Deep-Compact-Clustering%20Based%20Anomaly%20Detection%20Applied%20to%20Electromechanical%20Industrial%20Systems.pdf;jsessionid=72D97ADE1A990F0979D7A76E671D212F?sequence=1, (20220316), XP055902153 [A] 1-15 * figures 3, 4 * * section 3 *

DOI:   http://dx.doi.org/10.3390/s21175830
 [A]  - VIDYASAGAR SADHU ET AL, "Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, (20190628), XP081386849 [A] 1-15 * figure 3 * * section III *
by applicant   - FORGY, EDWARD W, "Cluster analysis of multivariate data: efficiency versus interpretability of classifications", Biometrics, (19650000), vol. 21, no. 3, pages 768 - 769, XP009011863
    - "Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis", Rousseeuw published in Computational and Applied Mathematics, (19870000), vol. 20, pages 53 - 65
    - BENTLEY, J.L., "Multidimensional binary search trees used for associative searching", Communications of the ACM, (19750000), vol. 18, no. 9, doi:10.1145/361002.361007, pages 509 - 517, XP058175972

DOI:   http://dx.doi.org/10.1145/361002.361007
    - MAHALANOBIS, PRASANTA CHANDRA, "On the generalised distance in statistics", Proceedings of the National Institute of Science of India, (19360000), vol. 2, no. 1, pages 49 - 55
    - KIM, "Multivariate Outliers and Decompositions of Mahalanobis Distance", Commun Statist. Theory Meth, (20000000), vol. 29, no. 7, pages 1511 - 1526
    - TUCKEY, JOHN W, Exploratory Data Analysis, Addison-Wesley Publishing Company Reading, Mass. - Menlo Park, (19770000), page 688
The EPO accepts no responsibility for the accuracy of data originating from other authorities; in particular, it does not guarantee that it is complete, up to date or fit for specific purposes.