Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/29280
Title: Dilation method for finding close roots of polynomials based on constrained learning neural networks
Authors: Huang, DS
Ip, HHS
Chi, Z 
Wong, HS
Keywords: Close roots
Complex constrained learning algorithm
Dilation
Feedforward neural networks
Polynomials
Root-finder
Issue Date: 2003
Publisher: Elsevier Science Bv
Source: Physics letters, section a : general, atomic and solid state physics, 2003, v. 309, no. 5-6, p. 443-451 How to cite?
Journal: Physics Letters, Section A: General, Atomic and Solid State Physics 
Abstract: In finding roots of polynomials, often two or more roots that are close together in solution space are very difficult to be resolved by a root-finder. To solve this problem, this Letter proposes a dilation method to transform the positions of roots in space so that all roots in space are pulled further apart. As a result, those close (including complex) roots can be readily resolved efficiently by a root-finder. In addition, in this Letter a complex version of constrained learning algorithm is derived. Moreover, our previously proposing feedforward neural network (FNN) root-finder is adopted to address the root finding issue. Finally, some satisfactory results that support our approach are presented.
URI: http://hdl.handle.net/10397/29280
ISSN: 0375-9601
DOI: 10.1016/S0375-9601(03)00216-0
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