Matlab-based Neural Network Introduction for Sensors Curriculum
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.
S. A. Mulder et al., "Matlab-based Neural Network Introduction for Sensors Curriculum," International Journal of Engineering Education: Special Edition on Matlab and Simulink in Engineering Education, Tempus Publications, Jan 2005.
Electrical and Computer Engineering
Mary K. Finley Missouri Endowment
National Science Foundation (U.S.)
Keywords and Phrases
Artificial Neural Networks (ANN); Sensors Curriculum
Article - Journal
© 2005 Tempus Publications, All rights reserved.
01 Jan 2005