Neural Networks as Cybernetic Systems - 3rd and revised edition

This third edition essentially compares with the 2nd one, but has been improved by correction of errors and by a rearrangement and minor expansion of the sections referring to recurrent networks. These changes hopefully allow for an easier comprehension of the essential aspects of this important domain that has received growing attention during the last years.

Neural Networks as Cybernetic Systems (3rd and revised edition) - Part I

Neural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology. This third edition essentially compares with the 2nd one, but has been improved by correction of errors and by a rearrangement and minor expansion of the sections referring to recurrent networks. These changes hopefully allow for an easier comprehension of the essential aspects of this important domain that has received growing attention during the last years.

Neural Networks as Cybernetic Systems (3rd and revised edition) - Part 2

eural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology. This third edition essentially compares with the 2nd one, but has been improved by correction of errors and by a rearrangement and minor expansion of the sections referring to recurrent networks. These changes hopefully allow for an easier comprehension of the essential aspects of this important domain that has received growing attention during the last years.

VuLF – Entwicklung eines Versuchsstandes zur Fehlerminimierung durch Fahrzeuganalyse

Fahrerlose Transportsysteme (FTS) kommen in der Intralogistik immer mehr zum Einsatz. Dabei wer-den neue Anforderungen an die FTS gestellt, die bisherige Aufgaben weit übersteigen. Der Transport von schweren Lasten und die Fahrt mehrere FTS in einer Formation sind dabei nur der Anfang einer Menge zukünftiger Einsatzgebiete. Große Probleme stellen dabei Schlupf und Verschleiß dar, die bisher noch kaum erforscht sind, welche die Performance der Fahrzeuge jedoch stark beeinträchtigen. Um diese Fehlerquellen besser verstehen zu können, wurde ein Versuchsstand entwickelt, mit dessen Hilfe Einzelfahrten aber auch Formationsfahrten in Bezug auf Schlupf und Verschleiß besser untersucht werden können. Dabei kann ein sehr breites Spektrum an Fahrzeugarten abgedeckt werden, da Parameter wie Lenksysteme oder Bereifung variabel gewählt werden können.