New Quasi-Deadbeat FIR Smoother for Discrete-Time State-Space Signal Models: An LMI Approach

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences ◽

10.1093/ietfec/e91-a.9.2671 ◽

2008 ◽

Vol E91-A (9) ◽

pp. 2671-2674 ◽

Author(s):

C. AHN

Keyword(s):

State Space ◽

Discrete Time ◽

Lmi Approach ◽

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$L_{2}-E$ FIR Smoothers for Deterministic Discrete-Time State–Space Signal Models

IEEE Transactions on Automatic Control ◽

10.1109/tac.2007.895890 ◽

2007 ◽

Vol 52 (5) ◽

pp. 927-932 ◽

Author(s):

Soohee Han ◽

Wook Hyun Kwon

Keyword(s):

State Space ◽

Discrete Time ◽

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A Robust FIR Filter for Linear Discrete-Time State–Space Signal Models With Uncertainties

IEEE Signal Processing Letters ◽

10.1109/lsp.2007.891839 ◽

2007 ◽

Vol 14 (8) ◽

pp. 553-556 ◽

Author(s):

Zhonghua Quan ◽

Soohee Han ◽

Wook Hyun Kwon

Keyword(s):

State Space ◽

Discrete Time ◽

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New Multi-Step FIR Predictors for State-Space Signal Models

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences ◽

10.1587/transfun.e92.a.1233 ◽

2009 ◽

Vol E92-A (4) ◽

pp. 1233-1236

Author(s):

ChoonKi AHN

Keyword(s):

State Space ◽

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A delay-dependent LMI approach to dynamics analysis of discrete-time recurrent neural networks with time-varying delays

Physics Letters A ◽

10.1016/j.physleta.2007.03.088 ◽

2007 ◽

Vol 368 (1-2) ◽

pp. 134-145 ◽

Author(s):

Qiankun Song ◽

Zidong Wang

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Recurrent Neural Networks ◽

Dynamics Analysis ◽

Time Varying ◽

Lmi Approach ◽

Delay Dependent

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The discrete time Biquad State Space structure: Low latency with high numerical fidelity

2015 American Control Conference (ACC) ◽

10.1109/acc.2015.7171161 ◽

2015 ◽

Author(s):

Daniel Y. Abramovitch

Keyword(s):

State Space ◽

Discrete Time ◽

Space Structure ◽

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A unified framework for modeling slow response self-powered neutron detectors with discrete-time state-space representation

2013 3rd International Conference on Advancements in Nuclear Instrumentation, Measurement Methods and their Applications (ANIMMA) ◽

10.1109/animma.2013.6728071 ◽

2013 ◽

Author(s):

Daowei Bi ◽

Dongling Xu ◽

Jiangtao Bu

Keyword(s):

State Space ◽

Discrete Time ◽

Space Representation ◽

Slow Response ◽

Unified Framework ◽

Neutron Detectors ◽

State Space Representation ◽

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Modeling the lift DC-DC converter in the state space discrete time

2005 European Conference on Power Electronics and Applications ◽

10.1109/epe.2005.219204 ◽

2005 ◽

Author(s):

F. Belloni ◽

P.G. Maranesi ◽

M. Riva

Keyword(s):

State Space ◽

Discrete Time ◽

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An LMI approach to robust fault detection filter design for discrete-time systems with model uncertainty

Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228) ◽

10.1109/cdc.2001.980421 ◽

2003 ◽

Author(s):

Maiying Zhong ◽

S.X. Ding ◽

Bingyong Tang ◽

Ping Zhang ◽

Torsten Jeinsch

Keyword(s):

Fault Detection ◽

Discrete Time ◽

Model Uncertainty ◽

Filter Design ◽

Lmi Approach ◽

Fault Detection Filter ◽

Discrete Time Systems ◽

Robust Fault Detection ◽

Time Systems ◽

Detection Filter

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Optimal guaranteed cost control of a class of nonlinear uncertain discrete-time systems: an LMI approach

2006 American Control Conference ◽

10.1109/acc.2006.1657521 ◽

2006 ◽

Author(s):

Zhe Dong ◽

Zheng You

Keyword(s):

Discrete Time ◽

Cost Control ◽

Guaranteed Cost Control ◽

Lmi Approach ◽

Discrete Time Systems ◽

Guaranteed Cost ◽

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Predictive Control of Discrete Time Stochastic Nonlinear State Space Dynamical Systems: A Particle Nonparametric Approach

Applied Mathematics & Optimization ◽

10.1007/s00245-017-9462-9 ◽

2017 ◽

Vol 80 (1) ◽

pp. 165-194

Author(s):

Jean-Pierre Vila ◽

Jean-Pierre Gauchi

Keyword(s):

Dynamical Systems ◽

State Space ◽

Predictive Control ◽

Discrete Time ◽

Nonparametric Approach ◽

Nonlinear State

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