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Gaetano Pasini

Researcher at University of Bologna

Publications -  77
Citations -  1054

Gaetano Pasini is an academic researcher from University of Bologna. The author has contributed to research in topics: Sampling (statistics) & Spectrum analyzer. The author has an hindex of 15, co-authored 76 publications receiving 1001 citations.

Papers
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Digital detection and fuzzy classification of partial discharge signals

TL;DR: In this article, a fuzzy classifier is used for the analysis of the acquired PD-pulse shape signals, and the result of the fuzzy classification is a cluster of signals homogeneous in terms of stochastic features of PD pulses.
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A modified Volterra series approach for nonlinear dynamic systems modeling

TL;DR: In this article, a modified Volterra series is proposed to model nonlinear dynamic systems under the assumption of short-term nonlinear memory effects, and the modified series enables a single-fold nonlinear convolution integral to be adopted also in the presence of strong nonlinearities.
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A nonlinear dynamic model for performance analysis of large-signal amplifiers in communication systems

TL;DR: A new nonlinear dynamic model of large-signal amplifiers based on a Volterra-like integral series expansion is described, which represents a generalization, to nonlinear systems with memory, of the widely-used amplitude/amplitude (AM/AM) and amplitude/phase (PM) conversion characteristics.
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Partial discharge inference by an advanced system. Analysis of online measurements performed on hydrogenerator

TL;DR: In this paper, a new system aimed at performing partial discharge measurements and condition assessment on electrical apparatus is presented, which is able to separate the conventional phase resolved partial discharge pattern into a series of sub-patterns, each of them containing partial discharge data generated by a single kind of defect.
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Low-cost DSP-based equipment for the real-time detection of transients in power systems

TL;DR: A novel solution for the real-time detection of transients in power systems is presented, which relies on a simple and robust algorithm that does not involve high computational burdens, does not require a high amount of memory, and is implemented on a low-cost DSP.