Spezielle Minimalrealisierungsformen der reellen positiven Matrix-Übertragungsfunktion / Special forms of minimal realization of the real positive matrix transfer function

1978 ◽  
Vol 26 (1-12) ◽  
Author(s):  
H.A. Nour Eldin
2007 ◽  
Vol 129 (5) ◽  
pp. 672-677
Author(s):  
Robin C. Redfield

Output variables of dynamic systems subject to random inputs are often quantified by mean-square calculations. Computationally for linear systems, these typically involve integration of the output spectral density over frequency. Numerically, this is a straightforward task and, analytically, methods exist to find mean-square values as functions of transfer function (frequency response) coefficients. These formulations offer analytical relationships between system parameters and mean-square response. This paper develops further analytical relationships in calculating mean-square values as functions of transfer function and state-space properties. Specifically, mean-square response is formulated from (i) system pole-zero locations, (ii) as a spectral decomposition, and (iii) in terms of a system matrix transfer function. Direct, closed-form relationships between response and these properties are afforded. These new analytical representations of the mean-square calculation can provide significant insight into dynamic system response and optimal design/tuning of dynamic systems.


2020 ◽  
pp. 1-3
Author(s):  
Afonin SM ◽  

The regulation and mechanical characteristics of the electromagnetoelastic actuator are obtained for control systems in nano physics and optics sciences for scanning microscopy, adaptive optics and nano biomedicine. The piezo actuator is used for nano manipulators. The matrix transfer function of the electromagnetoelastic actuator is received for nano physics and optics sciences


2019 ◽  
Vol 485 (2) ◽  
pp. 2407-2416 ◽  
Author(s):  
Lehman H Garrison ◽  
Daniel J Eisenstein

ABSTRACT We present a method for generating suites of dark matter halo catalogues with only a few N-body simulations, focusing on making small changes to the underlying cosmology of a simulation with high precision. In the context of blind challenges, this allows us to re-use a simulation by giving it a new cosmology after the original cosmology is revealed. Starting with full N-body realizations of an original cosmology and a target cosmology, we fit a transfer function that displaces haloes in the original so that the galaxy/HOD power spectrum matches that of the target cosmology. This measured transfer function can then be applied to a new realization of the original cosmology to create a new realization of the target cosmology. For a 1 per cent change in σ8, we achieve 0.1 per cent accuracy to $k = 1\, h\, \mathrm{Mpc}^{-1}$ in the real-space power spectrum; this degrades to 0.3 per cent when the transfer function is applied to a new realization. We achieve similar accuracy in the redshift-space monopole and quadrupole. In all cases, the result is better than the sample variance of our $1.1\, h^{-1}\, \mathrm{Gpc}$ simulation boxes.


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