Identification of stochastic linear systems via spectral analysis: reduced-order approximation, performance analysis and transfer function bias

Author(s):  
J.K. Tugnait
2001 ◽  
Vol 11 (07) ◽  
pp. 2051-2059 ◽  
Author(s):  
NICK T. KOUSSOULAS

The simplicity of structure of chaotic systems, combined with the richness of their output, inspires their use in modeling efforts. On the other hand, the difficulty of their analysis warrants approximation methods, especially since the absence, by definition, of well-defined limit sets prohibits, in general, a meaningful linearization. In this work we present some results, which can support a methodology founded on spectral analysis for approximating chaotic systems via stochastic linear systems. The main contribution is the use of spectral moments for identifying the location of embedded limit cycles and the spectrum-based validation of approximations.


2012 ◽  
Vol 22 (4) ◽  
pp. 451-465 ◽  
Author(s):  
Tadeusz Kaczorek

A new modified state variable diagram method is proposed for determination of positive realizations with reduced numbers of delays and without delays of linear discrete-time systems for a given transfer function. Sufficient conditions for the existence of the positive realizations of given proper transfer function are established. It is shown that there exists a positive realization with reduced numbers of delays if there exists a positive realization without delays but with greater dimension. The proposed methods are demonstrated on a numerical example.


2021 ◽  
pp. 1-1
Author(s):  
Amanda Spagolla ◽  
Cecilia F. Morais ◽  
Ricardo C. L. F. Oliveira ◽  
Pedro L. D. Peres

2015 ◽  
Vol 109 ◽  
pp. 110-118 ◽  
Author(s):  
Zhuo Zhang ◽  
Zexu Zhang ◽  
Shichun Yang

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