Time-Frequency Reassignment: From Principles to Algorithms

Flandrin, Patrick; Auger, François; Chassande–Mottin, E.

doi:10.1201/9781315220017-5

Cited by 47 publications

(35 citation statements)

References 25 publications

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“…The spatial spectrogram of the firing rate of each unit was computed at spatial frequencies (i.e., the frequency of repetition of its spatial firing pattern per physical lap) between 0.16/lap and 6/lap, using a sliding window of size 12 laps applied at increments of 5°. The spectrogram was further sharpened using the method of reassignment, which can be used when the input signal contains sparse periodic signal sources 39 . The original spectrogram was also thresholded to the mean + K times standard deviation (K between 1.1 and 2 based on visual inspection of the raw spectrogram) of its power at each spatial window; this thresholding was then applied to the sharpened spectrogram to improve the signal-to-noise ratio of the spatial frequency content.…”

Section: ‫ܩ‬ ൌmentioning

confidence: 99%

Recalibration of path integration in hippocampal place cells

Jayakumar

Madhav

Savelli

et al. 2018

Preprint

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13Hippocampal place cells are spatially tuned neurons that serve as elements of a 14 "cognitive map" in the mammalian brain 1 . To detect the animal's location, place cells 15 are thought to rely upon two interacting mechanisms: sensing the animal's position 16 relative to familiar landmarks 2,3 and measuring the distance and direction that the 17 animal has travelled from previously occupied locations 4-7 . The latter mechanism, 18 known as path integration, requires a finely tuned gain factor that relates the animal's 19 self-movement to the updating of position on the internal cognitive map, with external 20 landmarks necessary to correct positional error that eventually accumulates 8,9 . Path-21 integration-based models of hippocampal place cells and entorhinal grid cells treat 22the path integration gain as a constant 9-14 , but behavioral evidence in humans 23 suggests that the gain is modifiable 15 . Here we show physiological evidence from 24 hippocampal place cells that the path integration gain is indeed a highly plastic 25 variable that can be altered by persistent conflict between self-motion cues and 26 feedback from external landmarks. In a novel, augmented reality system, visual 27 landmarks were moved in proportion to the animal's movement on a circular track, 28 creating continuous conflict with path integration. Sustained exposure to this cue 29 conflict resulted in predictable and prolonged recalibration of the path integration 30 gain, as estimated from the place cells after the landmarks were extinguished. We 31 propose that this rapid plasticity keeps the positional update in register with the 32 60 Figure 1| Dome apparatus, experimental procedure, and sample data. a, Rendering of 61 dome apparatus. The dome shell is rendered semi-transparent for illustrative purposes. b, 62Photo of the apparatus. The dome is raised in the photo to allow visualization of the interior, 63but it is lowered as in (a) for the experiment. c, Illustration of experimental gain G. From the 64 same initial positions of the landmarks and rat, three different gain conditions are shown, in 65 both lab (top) and landmark (bottom) frames of reference. In each case, the rat runs 90° in 66 the lab frame. d, Profile of gain change and epochs during a typical session. An annular ring 67is always projected at the top of the dome (as shown in (a)) for illumination purposes, and is 68 not turned off even in Epoch 4. e, Representative firing rate maps for five different units from 69 five separate gain manipulation sessions, shown in the lab frame (top, middle rows) and 70 landmark frame (bottom row) during Epoch 3 (when the experimental gain was constant). 71 The plots in the top row are color scaled to their own individual maximum firing rates, 72 whereas the middle and bottom row plots are color scaled to the maximum firing rate of the 73 bottom plot of each pair. The difference in spatially averaged firing rates between landmark 74 and lab frames results from the distributed firing of the cells over the entire track in the l...

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Section: ‫ܩ‬ ൌmentioning

confidence: 99%

Recalibration of path integration in hippocampal place cells

Jayakumar

Madhav

Savelli

et al. 2018

Preprint

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“…In order to improve the scalograms readability and to reduce the interference caused by mutual energy between different signal components, an energy reassignment operation is performed. This technique involves assigning the calculated energy levels to the weighted centroid of the analysis windows rather than to their geometric center [18,[26][27][28][29]. In this way the energy peaks are more homogeneous in the different scales and have a lesser spread in the time-frequency plane.…”

Section: Signal Sparsification and Features Detectionmentioning

confidence: 99%

“…Since a correct estimate of these parameters is of the utmost importance for the flexibility-based damage detection, a variant of the original WS-TSVD-based procedure is proposed, aimed at further improving the obtained results. In particular, two steps are introduced within the original workflow: the first entails an energy reassignment process, widely applied in the field of signal analysis [18,[26][27][28][29], and the second consists of an energy-based filtering procedure.…”

Section: Introductionmentioning

confidence: 99%

On the Use of Singular Vectors for the Flexibility‐Based Damage Detection under the Assumption of Unknown Structural Masses

Quqa

Landi

Diotallevi

2018

Shock and Vibration

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The main purpose of this work is to investigate the usability of easily obtainable parameters instead of the modal traditional ones, in the context of a flexibility-based damage detection procedure, under the assumption of unknown structural masses. To this aim, a comparison is made between two different approaches: the first involves the calculation of the flexibility matrix by using traditional modal parameters, such as natural frequencies and modal vectors, normalized to unitary values, while the second involves the use of singular vectors, obtained through a simple matrix factorization. The modal parameters and the singular vectors necessary for the implementation of the damage detection procedure are evaluated through two different techniques: the Eigensystem Realization Algorithm and a wavelet-based procedure, for which a variant is proposed by introducing the energy reassignment concept into the original algorithm. Through the latter approach, in particular, it is possible to obtain a high number of singular vectors even in the case of reduced availability of sensors. The study is performed under the assumption of nonstationary excitation, in order to achieve general results, and the effectiveness of the procedures is evaluated through simulated tests regarding different structural schemes.

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“…The result is a higher resolution spatial image, which would normally have required a much higher order of input and a finer beamforming grid to produce. The approach is formulated in the SHD and is inspired by the time-frequency re-assignment principle for high-resolution imaging of time-frequency spectrograms [10]. Similar to time-frequency re-assignment, the proposed method first estimates the signal power for a certain point on the 2D manifold of directions, as given by the beamforming operation, while also estimating a new DoA for each focusing point.…”

Section: Introductionmentioning

confidence: 99%

Sharpening of Angular Spectra Based on a Directional Re-assignment Approach for Ambisonic Sound-field Visualisation

McCormack

Politis

Pulkki

2019

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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A method for computing and sharpening angular spectra, derived from low-order ambisonic signals, is presented in this paper, which is intended for high-resolution directional sound-field visualisation. The method relies on a re-assignment principle, whereby the directional energy for each grid point is assigned to a new direction, which corresponds to a direction-of-arrival (DoA) estimate within a spatially-localised region, centred around the respective grid point. This leads to the concentration of energy around the true sources, and hence, to sharper angular spectra than that of steered response power (SRP) beamformers of maximum directivity, with the same order of ambisonic input. It is demonstrated that the proposed method, when using loworder input, can achieve similar results to the SRP approach of much higher order.

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Time-Frequency Reassignment: From Principles to Algorithms

Cited by 47 publications

References 25 publications

Recalibration of path integration in hippocampal place cells

Recalibration of path integration in hippocampal place cells

On the Use of Singular Vectors for the Flexibility‐Based Damage Detection under the Assumption of Unknown Structural Masses

Sharpening of Angular Spectra Based on a Directional Re-assignment Approach for Ambisonic Sound-field Visualisation

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