Multi-jump resonance systems

Buscarino, Arturo; Famoso, Carlo; Fortuna, Luigi; Frasca, Mattia

doi:10.1080/00207179.2018.1535185

Cited by 16 publications

(5 citation statements)

References 10 publications

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“…Figure 3(a) shows that the performance of each method (except for the Differential Processing scheme) increases with the volume of the audio signal, but if the volume is too high, the performance decreases. This decrease is likely due to a nonlinear response of the speaker that produces sudden variations on the amplitude of the recovered signal with respect to the increase/decrease of the frequency of the input signal [19]. The performances of the Machine learning (ML) and Cross-correlation (CC) methods are comparable and represent the best choices.…”

Section: Resultsmentioning

confidence: 99%

“…3, some methods show a significant lower SINAD for certain frequencies. It would be interesting, for future work, to investigate if this effect can be linked to the occurrence of nonlinear resonance effects, such as the jump resonance [19] displayed by a nonlinear, non-autonomous system whose frequency response is characterised by one or more hysteresis regions, depending on the increasing/decreasing trend of the frequency at the input signal.…”

Section: Discussionmentioning

confidence: 99%

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Remote recovery of audio signals from videos of optical speckle patterns: a comparative study of signal recovery algorithms

et al. 2020

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Optical remote sensors are nowadays ubiquitously used, thanks to unprecedented advances in the last decade in photonics, machine learning and signal processing tools. In this work we study experimentally the remote recovery of audio signals from the silent videos of the movement of optical speckle patterns. This technique can be used even when in between the source and the receiver there is a medium that does not allow for the propagation of sound waves. We use a diode laser to generate a speckle pattern on the membrane of a loudspeaker and a low-cost CCD camera to record the video of the movement of the speckle pattern when the loudspeaker plays an audio signal. We perform a comparative analysis of six signal recovery algorithms. In spite of having different complexity and computational requirements, we find that the algorithms have (except for the simplest one) good performance in terms of the quality of the recovered signal. The best trade-off, in terms of computational costs and performance, is obtained with a new method that we propose, which recovers the signal from the weighted sum of the intensities of all the pixels, where the signs of the weights are determined by selecting a reference pixel and calculating the signs of the cross-correlations of the intensity of the reference pixel and the intensities of the other pixels.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Remote recovery of audio signals from videos of optical speckle patterns: a comparative study of signal recovery algorithms

et al. 2020

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“…Why the use of such scheme? The idea is that starting from the phenomenon of nonlinear jump resonance [5,6], well known as a source of potential drawbacks in automatic control problems [7], in the design of nonlinear filters can be exploited to obtain the desired useful behavior. Let us consider the the scheme in Fig.…”

Section: Design Of Multivalued Frequency Response Nonlinear Filtersmentioning

confidence: 99%

Design of multivalued frequency response filters by using nonlinear feedback

Bucolo

Buscarino

Fortuna

et al. 2023

NOLTA

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This contribution introduces the design of multivalued multiband frequency response filters exploiting nonlinear feedback design techniques. The interest in this topic is related to the possibility of analysing in real-time sinusoidal signals unveiling whether their main frequency components increase or decrease along different complex paths and in fixed sets of windows. This can be done by using the effects of frequency hysteresis, peculiar characteristic of the proposed devices.

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“…Moreover, recently the phenomenon of jump resonance has been actively used for frequency drifts detection (Buscarino et al, 2020). The electronic circuit realized following the schematic in Fig.…”

Section: Jump Resonancementioning

confidence: 99%