Journal
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 17, Issue 10, Pages 6864-6874Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.3047959
Keywords
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)
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Funding
- Innovation and Strength Project in Guangdong Province (Natural Science) [230419065]
- Key Laboratory of Digital Signal and Image Processing of Guangdong Province [2019GDDSIPL-01]
- Industry-University-Research Cooperation Education Project of Ministry of Education [201801328005]
- Guangdong Graduate Education Innovation Project, Graduate Summer School [2020SQXX19]
- Special Project in Key Fields of Universities in Department of Education of Guangdong Province [2019KZDZX1036]
- Doctoral Initiating Project of Guangdong Ocean University [E13428]
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A NCZNN model is designed to solve the time-varying complex-valued QP problem with linear equation constraint, with new complex-valued activation functions constructed. Simulation experiments verify the effectiveness and robustness of the NCZNN model. The model is also successfully applied to small target detection in remote sensing images.
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.
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