Abstract
The development of Artificial Neural Networks started 50 years ago, in order to understand the working of the brain. The microARTMAP, a new neural network architecture and the well-known Back Propagation based Multi-layer Perceptron (MLP) are compared in the context of hand gesture recognition. MicroARTMAP is a neural network paradigm where fuzzy logic is incorporated. Comparative study between BPN and MicroARTMAP is carried out on the basis of learning convergence and recognition accuracy [4], [66], [92], [112].
An Erratum can be found at http://dx.doi.org/10.1007/978-3-540-85130-1_11
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
David, V.K., Rajasekaran, S. (2009). Retracted Chapter: Gesture and Signature Recognition Using MicroARTMAP. In: Pattern Recognition using Neural and Functional Networks. Studies in Computational Intelligence, vol 160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85130-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-540-85130-1_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85129-5
Online ISBN: 978-3-540-85130-1
eBook Packages: EngineeringEngineering (R0)