View source for Publications:Neural modelling and control of the offset printing process

<div style='display: none'>
== Do not edit this section ==
</div>
{{PublicationSetupTemplate|Author=Antanas Verikas, Lars Bergman, Kerstin Malmqvist, Marija Bacauskiene
|PID=1393169
|Name=Verikas, Antanas (av) (0000-0003-2185-8973) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650));Bergman, Lars (lb) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938));Malmqvist, Kerstin (kermal) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938));Bacauskiene, Marija
|Title=Neural modelling and control of the offset printing process
|PublicationType=Conference Paper
|ContentType=Refereegranskat
|Language=eng
|Journal=
|JournalISSN=
|Status=
|Volume=
|Issue=
|HostPublication=Proceedings of the IASTED International Conference on Neural Networks and Computational Intelligence, NCI 2003, May 19-21, 2003, Cancun, Mexico
|Conference=IASTED International Conference on Neural Networks and Computational Intelligence (NCI 2003), Cancun, Mexico, May 19-21, 2003
|StartPage=130
|EndPage=135
|Year=2003
|Edition=
|Pages=
|City=
|Publisher=ACTA Press
|Series=
|SeriesISSN=
|ISBN=0889863474
|Urls=
|ISRN=
|DOI=
|ISI=
|PMID=
|ScopusId=2-s2.0-1542642394
|NBN=urn:nbn:se:hh:diva-40863
|LocalId=
|ArchiveNumber=
|Keywords=Image quality;Lithography;Mathematical models;Neural networks;Process control;Neural modeling;Offset lithographic printing;Offset printing
|Categories=Reglerteknik (20202)
|ResearchSubjects=
|Projects=
|Notes=
|Abstract=<p>In this paper, we present an approach to neural modelling and control of the offset lithographic printing process. A committee of neural networks is trained to measure the printing process output - the observable variables. From only one measurement the trained committee is capable of estimating the actual relative amount of each cyan, magenta, yellow, and black inks dispersed on paper in the measuring area. The obtained measurements are then further used by a neural model predictive control unit for generating control signals to compensate for colour deviation in offset newspaper printing. The experimental investigations performed have shown that the system developed achieves a higher printing process control accuracy than that usually obtained by the press operator.</p>
|Opponents=
|Supervisors=
|Examiners=
|Patent=
|ThesisLevel=
|Credits=
|Programme=
|Subject=
|Uppsok=
|DefencePlace=
|DefenceLanguage=
|DefenceDate=
|CreatedDate=2020-02-14
|PublicationDate=2020-02-14
|LastUpdated=2020-02-14
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:1393169}}
<div style='display: none'>

== Keep all hand-made modifications below ==
</div>{{PublicationDisplayTemplate}}