Abstract
An analog sequential architecture for efficient neuro-fuzzy models implementation is proposed. The best features of digital and analog domains are combined to provide a high degree of flexibility (in terms of number of inputs, number of membership functions per input and number of fuzzy rules) when handling real world tasks. The performance estimations show a good area/throughput ratio, thus making the architecture suitable for a wide range of applications.
Preview
Unable to display preview. Download preview PDF.
References
L.A. Zadeh, “Fuzzy Sets”, Information and Control, 8, pps. 338–353, 1965.
M.J. Patyra, J.L. Grantner, K. Koster, “Digital Fuzzy Logic Controller: Design and Implementation”, IEEE Transactions on Fuzzy Systems, Vol. 4, No. 4, pps.439–459, Nov. 1996.
H. Eichfeld, T. Künemund, M. Menke, “A 12b General-Purpose Fuzzy Logic Controller Chip”, IEEE Transactions on Fuzzy Systems, Vol. 4, No. 4, pps.460–475, November 1996.
S. Guo, L. Peters, H. Surmann, “Design and Application of an Analog Fuzzy Logic Controller”, IEEE Transactions on Fuzzy Systems, Vol. 4, No. 4, pps. 429–438, November 1996.
T. Yamakawa, “A Fuzzy Inference Engine in Nonlinear Analog Mode and its Application to a Fuzzy Logic Controller”, IEEE Transactions on Neural Networks, Vol. 4, pps. 496–522, May 1993.
J.M. Moreno, F. Castillo, J. Cabestany, J. Madrenas, A. Napieralski, “An Analog Systolic Neural Processing Architecture”, IEEE Micro, Vol. 14, No. 3, pps. 51–59, June 1994.
T. Takagi, M. Sugeno, “Fuzzy Idendification of Systems and its Application to Modeling and Control”, IEEE Transactions on Systems, Man and Cybernetics, Vol. 15, pps. 116–132, 1985.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Moreno, J.M., Madrenas, J., Alarcón, E., Cabestany, J. (1997). Analog sequential architecture for neuro-fuzzy models VLSI implementation. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020314
Download citation
DOI: https://doi.org/10.1007/BFb0020314
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63631-1
Online ISBN: 978-3-540-69620-9
eBook Packages: Springer Book Archive