Non-negative matrix factorization （NMF） is a technique for dimensionality reduction by placing non-negativity constraints on the matrix. Based on the PARAFAC model, NMF was extended for three-dimension data decompos...Non-negative matrix factorization （NMF） is a technique for dimensionality reduction by placing non-negativity constraints on the matrix. Based on the PARAFAC model, NMF was extended for three-dimension data decomposition. The three-dimension nonnegative matrix factorization （NMF3） algorithm, which was concise and easy to implement, was given in this paper. The NMF3 algorithm implementation was based on elements but not on vectors. It could decompose a data array directly without unfolding, which was not similar to that the traditional algorithms do, It has been applied to the simulated data array decomposition and obtained reasonable results. It showed that NMF3 could be introduced for curve resolution in chemometrics.展开更多
This paper deals with the problem of designing a robust discrete output-feedback based repetitive-control system for a class of linear plants with periodic uncertainties. The periodicity of the repetitive-control syst...This paper deals with the problem of designing a robust discrete output-feedback based repetitive-control system for a class of linear plants with periodic uncertainties. The periodicity of the repetitive-control system is exploited to establish a two-dimensional （2D） model that converts the design problem into a robust stabilization problem for a discrete 2D system. By employing Lyapunov stability theory and the singular-value decomposition of the output matrix, a linear-matrix-inequality （LMI） based stability condition is derived. The condition can be used directly to design the gains of the repetitive controller. Two tuning parameters in the LMI enable the preferential adjustment of control and learning. A numerical example illustrates the design procedure and demonstrates the validity of the method.展开更多
Industry and academia have been making great efforts in improving refresh rates and resolutions of display devices to meet the ever increasing needs of consumers for better visual quality.As a result,many modem displa...Industry and academia have been making great efforts in improving refresh rates and resolutions of display devices to meet the ever increasing needs of consumers for better visual quality.As a result,many modem displays have spatial and temporal resolutions far beyond the discern capability of human visual systems.Thus,leading to the possibility of using those display-eye redundancies for innovative usages.Tempo-ral/spatial psycho-visual modulation(TPVM/SPVM)was proposed to exploit those redundancies to generate multiple visual percepts for different viewers or to transmit non-visual data to computing devices without affecting normal viewing.This paper reviews the STPVM technology from both conceptual and algorithmic perspectives,with exemplary applications in multiview display,display with visible light communication,etc.Some possible future research directions are also identified.展开更多
文摘Non-negative matrix factorization （NMF） is a technique for dimensionality reduction by placing non-negativity constraints on the matrix. Based on the PARAFAC model, NMF was extended for three-dimension data decomposition. The three-dimension nonnegative matrix factorization （NMF3） algorithm, which was concise and easy to implement, was given in this paper. The NMF3 algorithm implementation was based on elements but not on vectors. It could decompose a data array directly without unfolding, which was not similar to that the traditional algorithms do, It has been applied to the simulated data array decomposition and obtained reasonable results. It showed that NMF3 could be introduced for curve resolution in chemometrics.
基金supported by National Natural Science Foundation of China(Nos.61210011and61203010)National Science Fund for Distinguished Youth Scholars of China(No.60425310)+1 种基金Scientific Research Fund of Hunan Provincial Education Department(No.12B044)Hunan Natural Science Foundation(No.11JJ4059)
文摘This paper deals with the problem of designing a robust discrete output-feedback based repetitive-control system for a class of linear plants with periodic uncertainties. The periodicity of the repetitive-control system is exploited to establish a two-dimensional （2D） model that converts the design problem into a robust stabilization problem for a discrete 2D system. By employing Lyapunov stability theory and the singular-value decomposition of the output matrix, a linear-matrix-inequality （LMI） based stability condition is derived. The condition can be used directly to design the gains of the repetitive controller. Two tuning parameters in the LMI enable the preferential adjustment of control and learning. A numerical example illustrates the design procedure and demonstrates the validity of the method.
基金would like thanks the National Natural Science Foundation of China(NSFC)for the support(Grant Nos.61901259,61831015,61771305,61927809,and U1908210)China Postdoctoral Science Foundation(BX2019208)。
文摘Industry and academia have been making great efforts in improving refresh rates and resolutions of display devices to meet the ever increasing needs of consumers for better visual quality.As a result,many modem displays have spatial and temporal resolutions far beyond the discern capability of human visual systems.Thus,leading to the possibility of using those display-eye redundancies for innovative usages.Tempo-ral/spatial psycho-visual modulation(TPVM/SPVM)was proposed to exploit those redundancies to generate multiple visual percepts for different viewers or to transmit non-visual data to computing devices without affecting normal viewing.This paper reviews the STPVM technology from both conceptual and algorithmic perspectives,with exemplary applications in multiview display,display with visible light communication,etc.Some possible future research directions are also identified.
