Isotonicity of minimizers in polychotomous discrete interval search via lattice programming

2000 ◽  
Vol 51 (1) ◽  
pp. 139-173 ◽  
Author(s):  
Karl Hinderer ◽  
Michael Stieglitz
Keyword(s):  
Lattice Programming ◽  
Discrete Interval

Frequent embedded subtree mining algorithm based on discrete interval

2009 ◽  
Vol 29 (4) ◽  
pp. 1120-1123
Author(s):  
Peng-cheng KONG ◽  
Ji-fu ZHANG
Keyword(s):  
Mining Algorithm ◽  
Discrete Interval

Stable Approximation of Discrete Interval Systems

2021 ◽  
Author(s):  
Aditya Prasad Padhy ◽  
Varsha Singh ◽  
Vinay Pratap Singh
Keyword(s):  
Discrete Interval ◽  
Interval Systems ◽  
Stable Approximation

On robust stability for uncertain neutral systems with non-differentiable interval time-varying discrete delay and nonlinear perturbations

2017 ◽  
Vol 11 (01) ◽  
pp. 1850007 ◽  
Author(s):  
Peerapongpat Singkibud ◽  
Kanit Mukdasai
Keyword(s):  
Robust Stability ◽  
Linear Matrix ◽  
Time Varying ◽  
Nonlinear Perturbations ◽  
Neutral Systems ◽  
Interval Time ◽  
Time Varying Delay ◽  
Robust Stability Analysis ◽  
Discrete Interval ◽  
Varying Delay

In this paper, we investigate the problem of delay-range-dependent robust stability analysis for uncertain neutral systems with interval time-varying delays and nonlinear perturbations. The restriction on the derivative of the discrete interval time-varying delay is removed. By applying the augmented Lyapunov–Krasovskii functional approach, new improved integral inequalities, descriptor model transformation, Leibniz–Newton formula and utilization of zero equation, new delay-range-dependent robust stability criteria are derived in terms of linear matrix inequalities (LMIs) for the considered systems. Numerical examples have shown to illustrate the significant improvement on the conservatism of the delay upper bound over some reported results.

Lattice programming methodology

1989 ◽  
pp. 96-107
Author(s):  
Kouichi Fukunaga ◽  
Shinichi Morishita
Keyword(s):  
Programming Methodology ◽  
Lattice Programming

A novel approach of fault-influencing factors analysis for high-voltage switchgears quality supervision based on industrial big data

2019 ◽  
Vol 233 (14) ◽  
pp. 2531-2546 ◽  
Author(s):  
Xianguang Kong ◽  
Jiantao Chang ◽  
Pei Wang ◽  
Siyi Gong ◽  
Yabin Shi ◽  
...  
Keyword(s):  
Big Data ◽  
Qualitative Analysis ◽  
Influencing Factors ◽  
High Voltage ◽  
Occurrence Probability ◽  
Analysis Method ◽  
Factors Analysis ◽  
Industrial Big Data ◽  
Discrete Interval ◽  
Interval Value

Fault-influencing factors analysis is an important part of the quality supervision process. There are double functions for high-voltage switchgears that switch off and protect electric circuits in power transmission lines. Such devices have serious impact on power grid–operating efficiency, factory operation, and resident life, which will cause economic losses. As it was difficult for traditional methods to analyze fault-influencing factors accurately and comprehensively, a novel method based on industrial big data was proposed to analyze high-voltage switchgears fault-influencing factors in the process of quality supervision in this article, which integrated the qualitative and quantitative analyses method. In this model, the Classification Based on Multiple Class-Association Rules based on Gaussian Mixture Model as the qualitative analysis method was adapted to analyze the whole life cycle of fault-influencing factors of high-voltage switchgears comprehensively, and supplied fault-influencing factors with discrete interval value ranges. The logistic regression method based on qualitative analysis was constructed to calculate fault occurrence probability quantitatively, including the single-fault occurrence probability and the multiple-faults joint occurrence probability. In addition, the single-fault occurrence probability was used to modify the discrete interval value ranges calculated by the qualitative analysis method, which could make the ranges more accurately. Consequently, the proposed method could provide important reference for high-voltage switchgears operation maintenance, and it would be possible to design accurate maintenance plans before equipment failure. The final instance demonstrates the effectiveness of the proposed methodology.

Sampled-Data Systems, Revisited: Reflections, Recollections, and Reassessments

1980 ◽  
Vol 102 (4) ◽  
pp. 208-217 ◽  
Author(s):  
E. I. Jury
Keyword(s):  
Digital Signal ◽  
Sampling Period ◽  
Data Systems ◽  
Sampled Data ◽  
Recent Emergence ◽  
New Development ◽  
Technological Developments ◽  
Discrete Interval ◽  
Discrete Theory ◽  
The Impact

A review of the progress made in sampled-data systems during the last thirty years is presented in this paper. In particular the impact of the discrete theory on the continuous counterpart is mentioned. Additionally, the limiting process of discrete system theory when the discrete interval (or the sampling period) goes to zero, is discussed. Recent emergence of digital signal processing and digital filters as an aftermath of sampled-data systems is brought into focus as well as the technological developments which aided in this new development. The paper concludes with a critical view of the past achievements in this field as well as indications of possible future developments.

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