The problem of the robust D-stability analysis for linear systems with parametric uncertainties is addressed. For matrix polytopes, new conditions via the affine parameter-dependent Lyapunov function of uncertain syst...The problem of the robust D-stability analysis for linear systems with parametric uncertainties is addressed. For matrix polytopes, new conditions via the affine parameter-dependent Lyapunov function of uncertain systems are developed with the benefit of the scalar multi-convex function. To be convenient for applications, such conditions are simplified into new linear matrix inequality （LMI） conditions, which can be solved by the powerful LMI toolbox. Numerical examples are provided to indicate that this new approach is less conservative than previous results for Hurwitz stability, Schur stability and D-stability of uncertain systems under certain circumstances.展开更多
A simple method for disturbance decoupling for matrix second-order linear systems is proposed directly in matrix second-order framework via Luenberger function observers based on complete parametric eigenstructure ass...A simple method for disturbance decoupling for matrix second-order linear systems is proposed directly in matrix second-order framework via Luenberger function observers based on complete parametric eigenstructure assignment. By introducing the H2 norm of the transfer function from disturbance to estimation error, sufficient and necessary conditions for disturbance decoupling in matrix second-order linear systems are established and are arranged into constraints on the design parameters via Luenberger function observers in terms of the closed-loop eigenvalues and the group of design parameters provided by the eigenstructure assignment approach. Therefore, the disturbance decoupling problem is converted into an eigenstructure assignment problem with extra parameter constraints. A simple example is investigated to show the effect and simplicity of the approach.展开更多
Kernel-based methods work by embedding the data into a feature space and then searching linear hypothesis among the embedding data points. The performance is mostly affected by which kernel is used. A promising way is...Kernel-based methods work by embedding the data into a feature space and then searching linear hypothesis among the embedding data points. The performance is mostly affected by which kernel is used. A promising way is to learn the kernel from the data automatically. A general regularized risk functional （RRF） criterion for kernel matrix learning is proposed. Compared with the RRF criterion, general RRF criterion takes into account the geometric distributions of the embedding data points. It is proven that the distance between different geometric distdbutions can be estimated by their centroid distance in the reproducing kernel Hilbert space. Using this criterion for kernel matrix learning leads to a convex quadratically constrained quadratic programming （QCQP） problem. For several commonly used loss functions, their mathematical formulations are given. Experiment results on a collection of benchmark data sets demonstrate the effectiveness of the proposed method.展开更多
电子信息系统小型化、轻量化、无人化、一体化的发展趋势要求电子封装持续减小尺寸、降低重量和减少功耗(SWaP,即Size,Weight and Power)。传统的基于可伐合金、铝合金和高硅铝的微电子封装材料难以同时满足大跨度热匹配、良好的钎焊与...电子信息系统小型化、轻量化、无人化、一体化的发展趋势要求电子封装持续减小尺寸、降低重量和减少功耗(SWaP,即Size,Weight and Power)。传统的基于可伐合金、铝合金和高硅铝的微电子封装材料难以同时满足大跨度热匹配、良好的钎焊与激光熔焊性能、高导热、高比刚度、高比强度和良好的可制造性,无法适应SWaP要求。功能梯度铝基复合材料综合了铝合金与铝硅、碳化硅铝等先进复合材料的优点,既具备大跨度热匹配、高导热率的特点,又具备精细加工和良好的激光熔焊等工艺性能,是新一代微电子封装材料的研究热点。本文综述了功能梯度铝基复合材料的优势、制备方法和封装应用情况,并对该材料制备与应用中存在的问题进行了总结,最后对其未来研究方向进行了展望。展开更多
基金supported by the National Natural Science Foundation of China (6090405161021002)
文摘The problem of the robust D-stability analysis for linear systems with parametric uncertainties is addressed. For matrix polytopes, new conditions via the affine parameter-dependent Lyapunov function of uncertain systems are developed with the benefit of the scalar multi-convex function. To be convenient for applications, such conditions are simplified into new linear matrix inequality （LMI） conditions, which can be solved by the powerful LMI toolbox. Numerical examples are provided to indicate that this new approach is less conservative than previous results for Hurwitz stability, Schur stability and D-stability of uncertain systems under certain circumstances.
文摘A simple method for disturbance decoupling for matrix second-order linear systems is proposed directly in matrix second-order framework via Luenberger function observers based on complete parametric eigenstructure assignment. By introducing the H2 norm of the transfer function from disturbance to estimation error, sufficient and necessary conditions for disturbance decoupling in matrix second-order linear systems are established and are arranged into constraints on the design parameters via Luenberger function observers in terms of the closed-loop eigenvalues and the group of design parameters provided by the eigenstructure assignment approach. Therefore, the disturbance decoupling problem is converted into an eigenstructure assignment problem with extra parameter constraints. A simple example is investigated to show the effect and simplicity of the approach.
基金supported by the National Natural Science Fundation of China (60736021)the Joint Funds of NSFC-Guangdong Province(U0735003)
文摘Kernel-based methods work by embedding the data into a feature space and then searching linear hypothesis among the embedding data points. The performance is mostly affected by which kernel is used. A promising way is to learn the kernel from the data automatically. A general regularized risk functional （RRF） criterion for kernel matrix learning is proposed. Compared with the RRF criterion, general RRF criterion takes into account the geometric distributions of the embedding data points. It is proven that the distance between different geometric distdbutions can be estimated by their centroid distance in the reproducing kernel Hilbert space. Using this criterion for kernel matrix learning leads to a convex quadratically constrained quadratic programming （QCQP） problem. For several commonly used loss functions, their mathematical formulations are given. Experiment results on a collection of benchmark data sets demonstrate the effectiveness of the proposed method.
文摘电子信息系统小型化、轻量化、无人化、一体化的发展趋势要求电子封装持续减小尺寸、降低重量和减少功耗(SWaP,即Size,Weight and Power)。传统的基于可伐合金、铝合金和高硅铝的微电子封装材料难以同时满足大跨度热匹配、良好的钎焊与激光熔焊性能、高导热、高比刚度、高比强度和良好的可制造性,无法适应SWaP要求。功能梯度铝基复合材料综合了铝合金与铝硅、碳化硅铝等先进复合材料的优点,既具备大跨度热匹配、高导热率的特点,又具备精细加工和良好的激光熔焊等工艺性能,是新一代微电子封装材料的研究热点。本文综述了功能梯度铝基复合材料的优势、制备方法和封装应用情况,并对该材料制备与应用中存在的问题进行了总结,最后对其未来研究方向进行了展望。
