Polynomial root finding and polynomiography, by Bahman Kalantari

2011 ◽  
Vol 5 (1) ◽  
pp. 48-49
Author(s):  
Gary Greenfield
Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1057
Author(s):  
Qifeng Wang ◽  
Xiaolin Hu ◽  
Xiaobao Deng ◽  
Nicholas E. Buris

Antenna element mutual coupling degrades the performance of Direction of Arrival (DoA) estimation significantly. In this paper, a novel machine learning-based method via Neural Tangent Kernel (NTK) is employed to address the DoA estimation problem under the effect of electromagnetic mutual coupling. NTK originates from Deep Neural Network (DNN) considerations, based on the limiting case of an infinite number of neurons in each layer, which ultimately leads to very efficient estimators. With the help of the Polynomial Root Finding (PRF) technique, an advanced method, NTK-PRF, is proposed. The method adapts well to multiple-signal scenarios when sources are far apart. Numerical simulations are carried out to demonstrate that this NTK-PRF approach can handle, accurately and very efficiently, multiple-signal DoA estimation problems with realistic mutual coupling.


2017 ◽  
Vol 18 ◽  
pp. 46-56 ◽  
Author(s):  
Kahina Ghidouche ◽  
Abderrahmane Sider ◽  
Raphaël Couturier ◽  
Christophe Guyeux

2010 ◽  
Vol 90 (9) ◽  
pp. 2723-2730 ◽  
Author(s):  
Mohamed Laid Bencheikh ◽  
Yide Wang ◽  
Hongyang He

2011 ◽  
Vol 434 (4) ◽  
pp. 854-879 ◽  
Author(s):  
Victor Y. Pan ◽  
Guoliang Qian ◽  
Ai-Long Zheng ◽  
Zhao Chen

1994 ◽  
Vol 23 (2) ◽  
pp. 415-436 ◽  
Author(s):  
Myong-Hi Kim ◽  
Scott Sutherland

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