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

2007 ◽  
Vol 52 (5) ◽  
pp. 927-932 ◽  
Author(s):  
Soohee Han ◽  
Wook Hyun Kwon
Keyword(s):  
State Space ◽  
Discrete Time ◽  
Signal Models

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

2007 ◽  
Vol 14 (8) ◽  
pp. 553-556 ◽  
Author(s):  
Zhonghua Quan ◽  
Soohee Han ◽  
Wook Hyun Kwon
Keyword(s):  
State Space ◽  
Discrete Time ◽  
Fir Filter ◽  
Signal Models

scholarly journals State space realizations robust to overloading for discrete-time LTI systems

2019 ◽  
Vol 156 ◽  
pp. 12-20 ◽  
Author(s):  
Shuichi Ohno ◽  
Yuichi Yoshimura
Keyword(s):  
State Space ◽  
Discrete Time

Criteria for the non-ergodicity of stochastic processes: application to the exponential back-off protocol

1987 ◽  
Vol 24 (02) ◽  
pp. 347-354 ◽  
Author(s):  
Guy Fayolle ◽  
Rudolph Iasnogorodski
Keyword(s):  
Stochastic Process ◽  
Markov Chain ◽  
Stochastic Processes ◽  
State Space ◽  
Discrete Time ◽  
Random Variables ◽  
Countable State Space ◽  
Countable State ◽  
New Criteria

In this paper, we present some simple new criteria for the non-ergodicity of a stochastic process (Yn ), n ≧ 0 in discrete time, when either the upward or downward jumps are majorized by i.i.d. random variables. This situation is encountered in many practical situations, where the (Yn ) are functionals of some Markov chain with countable state space. An application to the exponential back-off protocol is described.

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