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Content Provider | IEEE Xplore Digital Library |
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Author | Yifan Gao Cong Gu |
Copyright Year | 1999 |
Description | Author affiliation: Xi'an Highway Univ., Shaanxi, China (Yifan Gao) |
Abstract | Recently neural networks have been introduced to the microwave area as fast and flexible tools to microwave modeling, simulation and optimization. In this paper, a radial basis transfer function, combined with microwave empirical or semi-analytical information, is proposed. The microwave knowledge complements the capability of learning and generalization of neural networks by providing additional information that may not be adequately represented in a limited set of training data. Such knowledge becomes even more valuable when the neural model is used to extrapolate beyond training data region. |
Starting Page | 904 |
Ending Page | 905 |
File Size | 134255 |
Page Count | 2 |
File Format | |
ISBN | 0780357612 |
DOI | 10.1109/APMC.1999.833740 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1999-11-30 |
Publisher Place | Singapore |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Tellurium Gallium arsenide Scattering parameters Neural networks Predictive models MESFET circuits Training data Microwave theory and techniques Equivalent circuits Neurons |
Content Type | Text |
Resource Type | Article |
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