This paper employs the Direct Finite Element Squared(DFE2)method to develop Sparse Polynomial Chaos Expansions(SPCE)models for analyzing the electromechanical properties of multiscale piezoelectric structures.By incor...This paper employs the Direct Finite Element Squared(DFE2)method to develop Sparse Polynomial Chaos Expansions(SPCE)models for analyzing the electromechanical properties of multiscale piezoelectric structures.By incorporating variations in piezoelectric and elastic constants,the DFE2 method is utilized to simulate the statistical characteristics—such as expected values and standard deviations—of electromechanical properties,including Mises stress,maximum in-plane principal strain,electric potential gradient,and electric potential,under varying parameters.This approach achieves a balance between computational efficiency and accuracy.Different SPCE models are used to investigate the influence of piezoelectric and elastic constants on multiscale piezoelectric materials.Additionally,the multiscale parameterization study investigates how microscale material properties affect the macroscopic response of these structures and materials.展开更多
逆向思维是决策中常用的一种思维方法,但目前的反馈外延决策方法(Decision-making of Feedback Extension,DFE)均未考虑这一点。为此,在因素空间理论基础上,从对立概念角度出发构造了一种概念的外延逼近即反馈外延外包络,在此基础上提...逆向思维是决策中常用的一种思维方法,但目前的反馈外延决策方法(Decision-making of Feedback Extension,DFE)均未考虑这一点。为此,在因素空间理论基础上,从对立概念角度出发构造了一种概念的外延逼近即反馈外延外包络,在此基础上提出了基于反馈外延外包络的DFE决策方法。通过土壤肥力评级的实例验证了该方法的有效性和可行性。展开更多
In this paper performances of wavelet transform domain (WTD) adaptive equalizers based on the least mean￣square (LMS) algorithm are analyzed. The optimum Wiener solution, the condition of convergence, the minimum ...In this paper performances of wavelet transform domain (WTD) adaptive equalizers based on the least mean￣square (LMS) algorithm are analyzed. The optimum Wiener solution, the condition of convergence, the minimum mean square error (MSE) and the steady state excess MSE of the WTD adaptive equalizer are obtained. Constant and time varying convergence factor adaptive algorithms are studied respectively. Computational complexities of WTD LMS equalizers are given. The equalizer in WTD shows much better convergence performance than that of the conventional in time domain.展开更多
基金supported by the Zhumadian 2023 Major Science and Technology Special Project(Grant No.ZMDSZDZX2023002)the Postgraduate Education Reform and Quality Improvement Project of Henan Province(Grant No.YJS2023JD52).
文摘This paper employs the Direct Finite Element Squared(DFE2)method to develop Sparse Polynomial Chaos Expansions(SPCE)models for analyzing the electromechanical properties of multiscale piezoelectric structures.By incorporating variations in piezoelectric and elastic constants,the DFE2 method is utilized to simulate the statistical characteristics—such as expected values and standard deviations—of electromechanical properties,including Mises stress,maximum in-plane principal strain,electric potential gradient,and electric potential,under varying parameters.This approach achieves a balance between computational efficiency and accuracy.Different SPCE models are used to investigate the influence of piezoelectric and elastic constants on multiscale piezoelectric materials.Additionally,the multiscale parameterization study investigates how microscale material properties affect the macroscopic response of these structures and materials.
文摘逆向思维是决策中常用的一种思维方法,但目前的反馈外延决策方法(Decision-making of Feedback Extension,DFE)均未考虑这一点。为此,在因素空间理论基础上,从对立概念角度出发构造了一种概念的外延逼近即反馈外延外包络,在此基础上提出了基于反馈外延外包络的DFE决策方法。通过土壤肥力评级的实例验证了该方法的有效性和可行性。
文摘In this paper performances of wavelet transform domain (WTD) adaptive equalizers based on the least mean￣square (LMS) algorithm are analyzed. The optimum Wiener solution, the condition of convergence, the minimum mean square error (MSE) and the steady state excess MSE of the WTD adaptive equalizer are obtained. Constant and time varying convergence factor adaptive algorithms are studied respectively. Computational complexities of WTD LMS equalizers are given. The equalizer in WTD shows much better convergence performance than that of the conventional in time domain.
