Concept

Gabor wavelet

Related publications (19)

The Spectral Graph Wavelet Transform: Fundamental Theory and Fast Computation

The spectral graph wavelet transform (SGWT) defines wavelet transforms appropriate for data defined on the vertices of a weighted graph. Weighted graphs provide an extremely flexible way to model the data domain for a large number of important applications (such as data defined on vertices of social networks, transportation networks, brain connectivity networks, point clouds, or irregularly sampled grids). The SGWT is based on the spectral decomposition of the N×N graph Laplacian matrix L, where N is the nu

Springer2026

The effect of natural surfactants on air-water momentum exchange under light wind conditions in Lake Geneva

Ulrich Lemmin

Randomly distributed patches of smooth or rough/rippled surfaces are readily observed on most water bodies. Smooth surface patches are called natural slicks and typically form under low wind conditions (< 6 m s-1) when biogenic surfactants in the surface microlayer accumulate above a certain threshold. They may have spatial scales from tens of meters to kilometers. Slicks suppress the formation of wind-induced Gravity-Capillary Waves (GCW), leading to altered surface reflectance of light and microwaves and

2022

Serial dependence is related to the task and not the stimulus

There is a hot debate about the nature of serial dependence (SD), the tendency to judge stimulus features in a given trial as similar to the previous trial. It is often argued that SD reflects a mechanism to stabilize perception, combining features of similar stimuli over time. Here, we demonstrate that SD does not combine stimulus features at all, but only task-related information. We presented a random-dot kinematogram (RDK, 1000 ms, 90% coherence, radius of 1.25°) superimposed on a noisy Gabor patch (50%

2021

Perceptual decisions under stable visual input: absence of serial dependence and the build-up of adaptation

In serial dependence (SD), perceptual decisions are biased toward stimuli seen in the recent past. It is believed that SD originates from a perceptual prior that the world is stable and stimuli are correlated in time. Often, however, SD is observed in conditions that deviate from this prior —i.e., in tasks involving uncorrelated stimuli. It is therefore unclear to what extent perceptual priors are crucial for SD. If there is such a prior, one would expect larger SD for “stable”, i.e., correlated, streams of

2021

Air-water momentum exchange in Lake Geneva under light wind conditions: The effect of natural surfactants

Randomly distributed patches of smooth surfaces are readily observed on most water bodies. They are called natural slicks when biogenic surfactants in the surface microlayer accumulate above a certain threshold. Slicks typically form under low wind conditions (< 6 m s-1), having spatial scales from tens of meters to kilometers. They suppress the formation of wind-induced Gravity-Capillary Waves (GCW), leading to altered surface reflectance of light and microwaves, and can also affect near-surface convective

2020

Biologically plausible deep learning – but how far can we go with shallow networks?

Wulfram Gerstner, Johanni Michael Brea, Bernd Albert Illing

Training deep neural networks with the error backpropagation algorithm is considered implausible from a biological perspective. Numerous recent publications suggest elaborate models for biologically plausible variants of deep learning, typically defining s ...

2019

An Overview of a New Sensor Calibration Platform

Jan Skaloud

Inertial sensors have been employed in different types of applications in miniature embedded devices such as phones, watches, and small unmanned aerial vehicles. The stochastic structure of the error signal coming from these sensors is complex and needs to be determined for optimal fusion with other devices (e.g. GPS). The recently-proposed approach, Generalized Method of Wavelet Moments (GMWM) using the wavelet variance (WV), overcomes these limitations. The presented software platform can be used for stoc

2017

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Jan Skaloud

The proliferation of (low-cost) sensors provokes new challenges in data fusion. This is related to the correctness of stochastic characterization that is a prerequisite for optimal estimation of parameters from redundant observations. Different (statistical) methods were developed to estimate parameters of complex stochastic models. To cite a few, there is the maximum likelihood approach estimated via the so-called EM algorithm as well as a linear regression approach based on the log-log-representation of a

2017

Optimal Window and Lattice in Gabor Transform. Application to Audio Analysis

Benjamin Ricaud

This article deals with the use of optimal lattice and optimal window in Discrete Gabor Transform computation. In the case of a generalized Gaussian window, extending earlier contributions, we introduce an additional local window adaptation technique for n ...

Ieee2016

Beyond Allan Variance - GMWM Framework For Sensor Calibration

Jan Skaloud

Proposed 50 years ago for studying stability of oscillators, Allan Variance (AV) was accepted by IEEE as a standard for characterizing behavior of sensors. However, the inverse mapping, i.e. the estimation of noise-parameters from Allan Variance is less straightforward and considerably more difficult procedure. The parameters that can be reliably estimated via a linear regression on the AV log-log plots are limited to few possible models and this approach has recently been proven inconsistent. Alternative e

2015

Face Verification using Gabor Filtering and Adapted Gaussian Mixture Models

The search for robust features for face recognition in uncontrolled environments is an important topic of research. In particular, there is a high interest in Gabor-based features which have invariance properties to simple geometrical transformations. In this paper, we first reinterpret Gabor filtering as a frequency decomposition into bands, and analyze the influence of each band separately for face recognition. Then, a new face verification scheme is proposed, combining the strengths of Gabor filtering wi

GI-Edition2012

A Framework for Inertial Sensor Calibration Using Complex Stochastic Error Models

Jan Skaloud

Modeling and estimation of gyroscope and accelerometer errors is generally a very challenging task, especially for low-cost inertial MEMS sensors whose systematic errors have complex spectral structures. Consequently, identifying correct error-state parameters in a INS/GNSS Kalman filter / smoother becomes difficult when several processes are superimposed. In such situations, the classical identification approach via Allan Variance (AV) analyses fails due to the difficulty of separating the error-processes

Ieee2012

Optimally Localized Wavelets and Smoothing Kernels

Kunal Narayan Chaudhury

It is well-known that the Gaussian functions and, more generally, their modulations-translations (the Gabor functions) have the unique property of being optimally localized in space and frequency in the sense of Heisenberg's uncertainty principle. In this ...

EPFL2011

Filter Bank Fusion frames

In this paper we characterize and construct novel oversampled filter banks implementing fusion frames. A fusion frame is a sequence of orthogonal projection operators whose sum can be inverted in a numerically stable way. When properly designed, fusion fra ...

Institute of Electrical and Electronics Engineers2011

Monitoring of steel-lined pressure shafts using water-hammer records and wavelet filtering and decomposition

Anton Schleiss

The failure of steel liner of pressure shafts of hydropower plants can have catastrophic consequences. The partial or total loss of the liner support’s rigidity is characterized by a local change of the hydro-acoustic properties and creates reflection boundaries for the water waves. This paper presents a new monitoring method for detecting and locating weak reaches by processing reflected water-hammer waves at the boundaries of the shaft. These water-hammers are generated experimentally by a shut-off valve

2011

Time-scale joint representation of DNS and LES numerical data

Michel Deville, Emmanuel Leriche

A spectral analysis and a multiscale study are performed on the numerical data obtained from direct numerical simulation and large-eddy simulation of the turbulent flow in a cubical lid-driven cavity. The analyzed data or signals are picked at three specific points inside the cavity allowing to investigate three drastically different flow regimes over time: laminar, transitional and turbulent. In comparison with direct numerical simulation, large-eddy simulation not only have a reduced resolution in space b

2011

Face Verification using Gabor Filtering and Adapted Gaussian Mixture Models

Idiap2011

Analytical Footprints: Compact Representation of Elementary Singularities in Wavelet Bases

Michaël Unser, Dimitri Nestor Alice Van De Ville, Thierry Blu

We introduce a family of elementary singularities that are point-Holder alpha-regular. These singularities are self-similar and are the Green functions of fractional derivative operators; i.e., by suitable fractional differentiation, one retrieves a Dirac ...

Institute of Electrical and Electronics Engineers2010

Integrated Use of Time-Frequency Wavelet Decompositions for Fault Location in Distribution Networks: Theory and Experimental Validation

The paper presents a procedure for fault location in distribution networks, based on the use of the integrated time-frequency wavelet decompositions of the voltage transients associated with the fault-originated travelling waves. The proposed analysis of time-frequency wavelet decompositions has been found to improve the identification accuracy of the frequencies associated to the characteristic patterns of a fault location with respect to a sole frequency-domain wavelet analysis. Several laboratory fault t

2009

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Related publications (19)

Integrated Use of Time-Frequency Wavelet Decompositions for Fault Location in Distribution Networks: Theory and Experimental Validation

2009