MATLAB-Based Introduction to Neural Networks for Sensors Curriculum
Abstract
Specialists and non-specialists in artificial neural networks (ANN) must closely interact in many applications, including structural sensing. the non-specialists must be aware of ANN-specific terminology, capabilities, and connecting concepts for effective collaboration. an instructional approach for ANNs is described that progresses from practical concepts to guided MatLab-Based experimentation. Back propagation-trained multilayer perceptron neural networks are presented with an emphasis on parallel processing and training characteristics. the one-week instructional module has a lecture to convey terminology and structure, detailed examples to illustrate the training process, and guided application-Based exercises. the MatLab neural-networks toolbox provides a transparent learning environment in which the students focus on network design and training concepts rather than the tool itself. Learning effectiveness was evaluated in an applications-oriented sensors curriculum. Instructional resources including realistic problems are web-accessible. These resources may be adjusted for different degrees of challenge and for simpler or more realistic problem solving. © 2005 TEMPUS Publications.
Recommended Citation
R. Dua et al., "MATLAB-Based Introduction to Neural Networks for Sensors Curriculum," International Journal of Engineering Education, vol. 21, no. 4 PART I AND II, pp. 636 - 648, Tempus Publications, Sep 2005.
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
International Standard Serial Number (ISSN)
0949-149X
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Tempus Publications, All rights reserved.
Publication Date
28 Sep 2005