Feedforward Neural Network Methodology

The decade prior to publication has seen an explosive growth in com- tational speed and memory and a rapid enrichment in our understa- ing of arti?cial neural networks. These two factors have cooperated to at last provide systems engineers and statisticians with a working, prac- cal, and successful...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Fine, Terrence L. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: New York, NY : Springer New York, 1999.
Σειρά:Information Science and Statistics,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Objectives, Motivation, Background, and Organization
  • Perceptions—Networks with a Single Node
  • Feedforward Networks I: Generalities and LTU Nodes
  • Feedforward Networks II: Real-Valued Nodes
  • Algorithms for Designing Feedforward Networks
  • Architecture Selection and Penalty Terms
  • Generalization and Learning.