424 research outputs found
Uncovering the limits of uniqueness in sampled Gabor phase retrieval: A dense set of counterexamples in L2(ℝ)
Sampled Gabor phase retrieval — the problem of recovering a square-integrable signal from the magnitude of its Gabor transform sampled on a lattice — is a fundamental problem in signal processing, with important applications in areas such as imaging and audio processing. Recently, a classification of square-integrable signals which are not phase retrievable from Gabor measurements on parallel lines has been presented. This classification was used to exhibit a family of counterexamples to uniqueness in sampled Gabor phase retrieval. Here, we show that the set of counterexamples to uniqueness in sampled Gabor phase retrieval is dense in L2(ℝ), but is not equal to the whole of L2(ℝ) in general. Overall, our work contributes to a better understanding of the fundamental limits of sampled Gabor phase retrieval.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Analysi
Gabor Frames for Model Sets
We generalize three main concepts of Gabor analysis for lattices to the setting of model sets: fundamental identity of Gabor analysis, Janssen’s representation of the frame operator and Wexler–Raz biorthogonality relations. Utilizing the connection between model sets and almost periodic functions, as well as Poisson’s summations formula for model sets we develop a form of a bracket product that plays a central role in our approach. Furthermore, we show that, if a Gabor system for a model set admits a dual which is of Gabor type, then the density of the model set has to be greater than one.© The Author(s) 201
A fast learning algorithm for Gabor transformation
An adaptive learning approach for the computation of the coefficients of the generalized nonorthogonal 2-D Gabor transform representation is introduced in this correspondence. The algorithm uses a recursive least squares (RLS) type algorithm. The aim is to achieve minimum mean squared error for the reconstructed image from the set of the Gabor coefficients. The proposed RLS learning offers better accuracy and faster convergence behavior when compared with the least mean squares (LMS)-based algorithms. Applications of this scheme in image data reduction are also demonstrated
Palmprint Identification Using Gabor and Wide Principal Line Features
AbstractIn this paper proposed palmprint identification using Gabor features, Gabor and Wide Principal Line Image (WPLI) features. Extracted a fixed size ROI from palmprint images. Resize the extracted ROI into 64 x 64. Apply the Gabor filters to extract the features from the resized ROI. Dissimilarity distance is used to measure the dissimilarity between the query palmprint and database palmprint images. Experiments were conducted on Polyu Palmprint Database using Gabor features, Gabor and WPLI features. Experimental results shows that the proposed approach using Gabor and WPLI features obtains better results compared with the existing methods
The Mind/Body Connection
Physician and award winning author, Dr Gabor Mate, discusses his research at the intersection of addiction, science, psychology, and compassionhttps://digitalcommons.ciis.edu/publicprograms/1030/thumbnail.jp
Density of Gabor Systems Via the Short Time Fourier Transform
We apply a new approach to the study of the density of Gabor systems, and obtain a simple and straightforward proof to Ramanathan and Steger’s well-known result regarding the density of Gabor frames and Gabor Riesz sequences. Moreover, this point of view allows us to extend this result in several directions. The approach we use was first observed by Olevskii and the third author in their study of exponential systems, here we develop and simplify it further
Absorbing new subjects: holography as an analog of photography
I discuss the early history of holography and explore how perceptions, applications, and forecasts of the subject were shaped by prior experience. I focus on the work of Dennis Gabor (1900–1979) in England,Yury N. Denisyuk (b. 1924) in the Soviet Union, and Emmett N. Leith (1927–2005) and Juris Upatnieks (b. 1936) in the United States. I show that the evolution of holography was simultaneously promoted and constrained by its identification as an analog of photography, an association that influenced its assessment by successive audiences of practitioners, entrepreneurs, and consumers. One consequence is that holography can be seen as an example of a modern technical subject that has been shaped by cultural influences more powerfully than generally appreciated.
Conversely, the understanding of this new science and technology in terms of an older one helps
to explain why the cultural effects of holography have been more muted than anticipated by forecasters
between the 1960s and 1990s
Gabor Frames and Deep Scattering Networks in Audio Processing
This paper introduces Gabor scattering, a feature extractor based on Gabor frames and Mallat’s scattering transform. By using a simple signal model for audio signals, specific properties of Gabor scattering are studied. It is shown that, for each layer, specific invariances to certain signal characteristics occur. Furthermore, deformation stability of the coefficient vector generated by the feature extractor is derived by using a decoupling technique which exploits the contractivity of general scattering networks. Deformations are introduced as changes in spectral shape and frequency modulation. The theoretical results are illustrated by numerical examples and experiments. Numerical evidence is given by evaluation on a synthetic and a “real” dataset, that the invariances encoded by the Gabor scattering transform lead to higher performance in comparison with just using Gabor transform, especially when few training samples are available.© 2019 by the author
On the connection between uniqueness from samples and stability in Gabor phase retrieval
Gabor phase retrieval is the problem of reconstructing a signal from only the magnitudes of its Gabor transform. Previous findings suggest a possible link between unique solvability of the discrete problem (recovery from measurements on a lattice) and stability of the continuous problem (recovery from measurements on an open subset of R2). In this paper, we close this gap by proving that such a link cannot be made. More precisely, we establish the existence of functions which break uniqueness from samples without affecting stability of the continuous problem. Furthermore, we prove the novel result that counterexamples to unique recovery from samples are dense in L2(R) . Finally, we develop an intuitive argument on the connection between directions of instability in phase retrieval and certain Laplacian eigenfunctions associated to small eigenvalues.Analysi
Hamiltonian deformations of Gabor frames: First steps
AbstractGabor frames can advantageously be redefined using the Heisenberg–Weyl operators familiar from harmonic analysis and quantum mechanics. Not only does this redefinition allow us to recover in a very simple way known results of symplectic covariance, but it immediately leads to the consideration of a general deformation scheme by Hamiltonian isotopies (i.e. arbitrary paths of non-linear symplectic mappings passing through the identity). We will study in some detail an associated weak notion of Hamiltonian deformation of Gabor frames, using ideas from semiclassical physics involving coherent states and Gaussian approximations. We will thereafter discuss possible applications and extensions of our method, which can be viewed – as the title suggests – as the very first steps towards a general deformation theory for Gabor frames
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