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Home > Mathematics and Science Textbooks > Mathematics > Neuronale Netze: Theoretische Grundlagen Und Anwendung in Der Verkehrszeichenerkennung
Neuronale Netze: Theoretische Grundlagen Und Anwendung in Der Verkehrszeichenerkennung

Neuronale Netze: Theoretische Grundlagen Und Anwendung in Der Verkehrszeichenerkennung


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About the Book

Neuronale Netze sind ursprunglich aus der Biologie bekannt. Sie haben eine grobe Analogie zum Gehirn der Saugetiere. Kunstliche Neuronale Netze sind informationsverarbeitende Systeme. Sie bestehen aus einer grossen Anzahl einfacher Einheiten, den Neuronen, die sich Informationen in Form der Aktivierung der Neuronen uber gerichtete, gewichtete Verbindungen zusenden. Es sind massiv parallele, lernfahige Systeme. Neuronale Netze haben die Fahigkeit, eine Aufgabe selbstandig, anhand von Trainingsbeispielen, zu lernen. Uberblick uber die einzelnen Kapitel Kapitel 2.1 stellt die Grundlagen Neuronaler Netze dar. Dabei wird zuerst das Neuronale Netz definiert und seine Bestandteile erklart. Anschliessend werden verschiedene Netzstrukturen definiert. Kapitel 2.2 zeigt, welche Funktionen mittels Neuronaler Netze darstellbar sind. In Kapitel 3 werden verschiedene Lernverfahren fur Feedforward Netze dargestellt. Dabei wird das Training Neuronaler Netze als unrestringiertes Optimierungsproblem dargestellt. In den Lernverfahren wird auf die Theorie und teilweise auch auf die Konvergenz eingegangen. Dabei werden auch Vor- und Nachteile der Verfahren angesprochen. In Kapitel 4 werden verschiedene rekurrente Neuronale Netze dargestellt. Anschliessend werden verschiedene Lernverfahren fur diese Netze erlautert, die sich aus den Verfahren fur Feedforward Netze ableiten lassen. Ausserdem wird in Kapitel 4.6 die Stabilitat rekurrenter Neuronaler Netze untersucht. In Kapitel 4.7 wird die Boltzmann Maschine als eine Anwendung des Hopfield-Netzes mit einem, auf der Idee des Simulated Annealing beruhenden, Lernverfahren erlautert. Kapitel 5 stellt Verfahren zur Minimierung von Neuronalen Netzen vor. Kapitel 6 zeigt eine Anwendung Neuronaler Netze in der Verkehrszeichenerkennung. Es wird erklart, wie die Bilder bearbeitet und die Trainingsmuster erstellt wurden. Dann wurden die Neuronalen Netze mit Hilfe des Stuttgarter Neuronale Netze Simulators erstellt, trainiert und anhand von Testbildern getestet. Anschliessend wurde gezeigt, wie man ein vorhandenes Neuronales Netz erweitern kann. Diplomarbeit aus dem Jahr 2004 im Fachbereich Mathematik - Angewandte Mathematik, Note: 1.7, Universitat Bayreuth (Fakultat fur Mathematik und Physik), Sprache: Deu


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Product Details
  • ISBN-13: 9783638297721
  • Publisher: Grin Verlag
  • Publisher Imprint: Grin Verlag
  • Language: German
  • Sub Title: Theoretische Grundlagen Und Anwendung in Der Verkehrszeichenerkennung
  • ISBN-10: 3638297721
  • Publisher Date: 01 Jan 2004
  • Binding: Digital (delivered electronically)
  • No of Pages: 149


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