Topic
Transfer function
About: Transfer function is a research topic. Over the lifetime, 14362 publications have been published within this topic receiving 214983 citations. The topic is also known as: system function & network function.
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TL;DR: In this article, the scalar three-dimensional optical transfer function without using the paraxial approximation was derived for a partially coherent system with equal condenser and objective apertures and the coherent transfer function for a confocal transmission system.
Abstract: The scalar three-dimensional optical transfer function is derived without using the paraxial approximation. The weak-object transfer function for a partially coherent system with equal condenser and objective apertures and the coherent transfer function for a confocal transmission system are of identical form. The coherent transfer function of a confocal reflection system is also derived. Both uniform angular illumination and systems obeying the sine condition are considered. In all cases the transfer functions can be expressed analytically.
112 citations
TL;DR: In this paper, the problem of computing the frequency response of linear systems with parametric perturbation is addressed, and the results are useful in determining the H∞ norm, gain margin and phase margin and in improving the diagonal dominance of uncertain systems.
111 citations
TL;DR: The classical methods of frequency and spectral analysis are shown to be related to the well-known time domain methods of prediction error type via a common ''empirical transfer function estimate,'' and frequency domain weighting function determines the distribution of bias in case the true system cannot be exactly described within the chosen model set.
111 citations
TL;DR: In this article, two multi-input multi-output (MIMO) procedures for the identification of low-order state space models of power systems, by probing the network in open loop with low-energy pulses or random signals, are presented.
Abstract: The paper studies two multi-input multi-output (MIMO) procedures for the identification of low-order state space models of power systems, by probing the network in open loop with low-energy pulses or random signals. Although such data may result from actual measurements, the development assumes simulated responses from a transient stability program, hence benefiting from the existing large base of stability models. While pulse data is processed using the eigensystem realization algorithm, the analysis of random responses is done by means of subspace identification methods. On a prototype Hydro-Quebec power system, including SVCs, DC power lines, series compensation, and more than 1100 buses, it is verified that the two approaches are equivalent only when strict requirements are imposed on the pulse length and magnitude. The 10th-order equivalent models derived by random-signal probing allow for effective tuning of decentralized power system stabilizers (PSSs) able to damp both local and very slow inter-area modes.
110 citations
TL;DR: In this paper, a decoupling control system design for high-dimensional multi-input, multi-output (MIMO) processes is presented based on the Relative Normalized Gain Array (RNGA), an equivalent Transfer Function (ETF) for each element in the transfer function matrix was derived for the closed-loop control system and was used to approximate the inverse of the process transfer function.
110 citations