Highly Efficient Automatic Synthesis of a Millimeter-Wave On-Chip Deformable Spiral Inductor Using a Hybrid Knowledge-Guided and Data-Driven Technique
Author:
Affiliation:
1. State Key Laboratory of Millimeter Waves and the School of Information Science and Engineering, Southeast University, Nanjing, China
2. COT Design Department, Hisilicon Technologies Company Ltd., Shenzhen, China
Funder
National Natural Science Foundation of China
ZhiShan Scholar Program of Southeast University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Software
Link
http://xplorestaging.ieee.org/ielx7/43/10325328/10178110.pdf?arnumber=10178110
Reference33 articles.
1. Synthesis of Integrated Passive Components for High-Frequency RF ICs Based on Evolutionary Computation and Machine Learning Techniques
2. Automated Spiral Inductor Design by a Calibrated PI Network with Manifold Mapping Technique
3. Application of Artificial Neural Networks to Broadband Antenna Design Based on a Parametric Frequency Model
4. Neural network-based modeling and design of on-chip spiral inductors
5. Artificial neural networks for RF and microwave design—From theory to practice;zhang;IEEE Trans Microw Theory Tech,2003
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