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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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Book ChapterDOI
TL;DR: In this paper, it is shown that the phase of the transfer function can be estimated under broad conditions and the asymptotic behavior of a phase estimate is determined under broad assumptions.
Abstract: NonGaussian linear processes are considered. It is shown that the phase of the transfer function can be estimated under broad conditions. This is not true of Gaussian linear processes and in this sense Gaussian linear processes are atypical. The asymptotic behavior of a phase estimate is determined. The phase estimates make use of bispectral estimates. These ideas are applied to a problem of deconvolution which is effective even when the transfer function is not minimum phase. A number of computational illustrations are given.

367 citations

Book
26 Nov 2008
TL;DR: Linear Periodic Systems as mentioned in this paper, Floquet Theory and Stability, Structural Properties, Periodic Transfer Function and BIBO Stability, Time-invariant Reformulations, State-Space Realization, Zeros, Poles and the Delay Structure.
Abstract: Linear Periodic Systems- Floquet Theory and Stability- Structural Properties- Periodic Transfer Function and BIBO Stability- Time-invariant Reformulations- State-Space Realization- Zeros, Poles, and the Delay Structure- Norms of Periodic Systems- Factorization and Parametrization- Stochastic Periodic Systems- Filtering and Deconvolution- Stabilization and Control

367 citations

Journal ArticleDOI
01 Jul 1984
TL;DR: In this paper, the authors discuss the implementation of fiber-optic lattice structures incorporating singlemode fibers and directional couplers, and show that the pole of the system transfer function with the largest magnitude is simple and positive-valued (in the Z-plane), and that the magnitude of the frequency response can nowhere exceed its value at the origin.
Abstract: We discuss the implementation of fiber-optic lattice structures incorporating single-mode fibers and directional couplers. These fiber structures can be used to perform various high-speed time-domain and frequency-domain functions such as matrix operations and frequency filtering. In this paper we mainly consider systems in which the signals (optical intensities) and coupling coefficients are nonnegative quantities; these systems fit well in the theory of positive systems. We use this theory to conclude, for example, that for such systems the pole of the system transfer function with the largest magnitude is simple and positive-valued (in the Z-plane), and that the magnitude of the frequency response can nowhere exceed its value at the origin. We also discuss the effects of various noise phenomena on the performance of fiber-optic signal processors, particularly considering the effects of laser source phase fluctuations. Experimental results are presented showing that the dynamic range of the fiber systems, discussed in this paper, is limited, not by the laser source intensity noise or shot noise, but by the laser phase-induced intensity noise. Mathematical analyses of lattice structures as well as additional applications are also presented.

362 citations

Journal ArticleDOI
TL;DR: The system identification schemes using Laguerre models are extended and generalized to Kautz models, which correspond to representations using several different possible complex exponentials, and linear regression methods to estimate this sort of model from measured data are analyzed.
Abstract: In this paper, the problem of approximating a linear time-invariant stable system by a finite weighted sum of given exponentials is considered. System identification schemes using Laguerre models are extended and generalized to Kautz models, which correspond to representations using several different possible complex exponentials. In particular, linear regression methods to estimate this sort of model from measured data are analyzed. The advantages of the proposed approach are the simplicity of the resulting identification scheme and the capability of modeling resonant systems using few parameters. The subsequent analysis is based on the result that the corresponding linear regression normal equations have a block Toeplitz structure. Several results on transfer function estimation are extended to discrete Kautz models, for example, asymptotic frequency domain variance expressions. >

359 citations

Journal ArticleDOI
TL;DR: In this paper, the transfer functions of abstract linear systems are defined via a generalization of a theorem of Foures and Segal, and the main result is a necessary and sufficient condition for an abstract linear system to be regular, in terms of its transfer function.
Abstract: We recall the main facts about the representation of regular linear systems, essentially that they can be described by equations of the form x(t) = Ax(t) + Bu(t), y(t) = Cx(t) + Du(t) , like finite dimensional systems, but now A, B and C are in general unbounded operators. Regular linear systems are a subclass of abstract linear systems. We define transfer functions of abstract linear systems via a generalization of a theorem of Foures and Segal. We prove a formula for the transfer function of a regular linear system, which is similar to the formula in finite dimensions. The main result is a (simple to state but hard to prove) necessary and sufficient condition for an abstract linear system to be regular, in terms of its transfer function. Other conditions equivalent to regularity are also obtained. The main result is a consequence of a new Tauberian theorem, which is of independent interest.

357 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023351
2022810
2021329
2020421
2019461
2018493