A MLMVN with Arbitrary Complex-Valued Inputs and a Hybrid Testability Approach for the Extraction of Lumped Models Using FRA
Author:
Affiliation:
1. Manhattan College , Riverdale, New York , USA
2. Dept. of Information Engineering , University of Florence , Firenze , Italy
Abstract
Publisher
Walter de Gruyter GmbH
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Hardware and Architecture,Modeling and Simulation,Information Systems
Link
https://www.sciendo.com/pdf/10.2478/jaiscr-2018-0021
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3. [3] S. L. Goh, M. Chen, D. H. Popovic, K. Aihara, D. Obradovic and D. P. Mandic, Complex Valued Forecasting of Wind Profile, Renewable Energy, vol. 31, pp. 1733-1750, Sep. 2006.
4. [4] A. Handayani, A.B.Suksmono, T.L.R.Mengko, and A.Hirose, Blood Vessel Segmentation in Complex-Valued Magnetic Resonance Images with Snake Active Contour Model, International Journal of EHealth and Medical Communications, vol. 1, no. 1, pp. 41-52, Jan. 2010.
5. [5] G. Avitabile, B. Chellini, G. Fedi, A. Luchetta and S. Manetti, A neural architecture for the parameter extraction of high frequency devices, in Proc. of IEEE Int. Symposium on Circuits and Systems (ISCAS), Sidney, Australia, 2001, pp. 577-580.
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