文献类型：期刊文献

英文题名：Nonconvex and Bound Constraint Zeroing Neural Network for Solving Time-Varying Complex-Valued Quadratic Programming Problem

作者：Jiang, Chengze[1,2];Xiao, Xiuchun[1,2];Liu, Dazhao[1,2];Huang, Haoen[1,2];Xiao, Hua[1,2];Lu, Huiyan[3]

机构：[1]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Peoples R China;[2]Guangdong Prov Engn & Technol Res Ctr, Marine Remote Sensing & Informat Technol, Zhanjiang 524088, Peoples R China;[3]Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China

年份：2021

卷号：17

期号：10

起止页码：6864

外文期刊名：IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

收录：SCI-EXPANDED(收录号：WOS:000673414500029)、、EI(收录号：20210209761553)、Scopus(收录号：2-s2.0-85099109710)、WOS

基金：This work was supported in part by the Innovation and Strength Project in Guangdong Province (Natural Science) under Grant 230419065, in part by the Key Laboratory of Digital Signal and Image Processing of Guangdong Province (2019GDDSIPL-01), in part by the Industry-UniversityResearch Cooperation Education Project of Ministry of Education under Grant 201801328005, in part by the Guangdong Graduate Education Innovation Project, Graduate Summer School (2020SQXX19), in part by the Special Project in Key Fields of Universities in Department of Education of Guangdong Province (2019KZDZX1036), and in part by the Doctoral Initiating Project of Guangdong Ocean University under Grant E13428. Paper no. TII-20-4431.

语种：英文

外文关键词：Mathematical model; Informatics; Numerical models; Quadratic programming; Synthetic aperture radar; Robustness; Technological innovation; Complex domain; nonconvex and bound constraint; small target detection; time-varying quadratic programming (QP); zeroing neural network (ZNN)

外文摘要：Many methods are known to solve the problem of real-valued and static quadratic programming (QP) effectively. However, few of them are still useful to solve the time-varying QP problem in the complex domain. In this study, a nonconvex and bound constraint zeroing neural network (NCZNN) model is designed and theorized to solve the time-varying complex-valued QP with linear equation constraint. Besides, we construct several new types of nonconvex and bound constraint complex-valued activation functions by extending real-valued activation functions to the complex domain. Subsequently, corresponding simulation experiments are conducted, and the simulation results verify the effectiveness and robustness of the proposed NCZNN model. Moreover, the model proposed in this article is further applied to solve the issue of small target detection in remote sensing images, which is modeled to QP problem with linear equation constraint by a serial of conversions based on constrained energy minimization algorithm.