Matlab-based Neural Network Introduction 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 webaccessible. These resources may be adjusted for different degrees of challenge and for simpler or more realistic problem solving.

Department(s)

Electrical and Computer Engineering

Sponsor(s)

Mary K. Finley Missouri Endowment
National Science Foundation (U.S.)

Keywords and Phrases

Artificial Neural Networks (ANN); Sensors Curriculum

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2005 Tempus Publications, All rights reserved.

Publication Date

01 Jan 2005

Link to Full Text

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