Eugene Brevdo - Academia.edu (original) (raw)

Papers by Eugene Brevdo

Wavelet transforms and machine learning tools can be used to assist art experts in the stylistic ... more Wavelet transforms and machine learning tools can be used to assist art experts in the stylistic analysis of paintings. A dual-tree complex wavelet transform, Hidden Markov Tree modeling and Random Forest classifiers are used here for a stylistic analysis of Vincent van Gogh's paintings with results on two stylometry challenges that concern "dating, resp. extracting distinguishing features".

We analyze the stability properties of the Synchrosqueezing transform, a time-frequency signal an... more We analyze the stability properties of the Synchrosqueezing transform, a time-frequency signal analysis method that can identify and extract oscillatory components with time-varying frequency and amplitude. We show that Synchrosqueezing is robust to bounded perturbations of the signal and to Gaussian white noise. These results justify its applicability to noisy or nonuniformly sampled data that is ubiquitous in engineering and the natural sciences. We also describe a practical implementation of Synchrosqueezing and provide guidance on tuning its main parameters.

2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010

We propose an algorithm for detecting bridges and estimating geodesic distances from a set of noi... more We propose an algorithm for detecting bridges and estimating geodesic distances from a set of noisy samples of an underlying manifold. Finding geodesics on a nearest neighbors graph is known to fail in the presence of bridges. Our method detects bridges using global statistics via a Markov random walk and denoises the nearest neighbors graph using "surrogate" weights. We show experimentally that our method outperforms methods based on local neighborhood statistics.

Proceedings of SPIE - The International Society for Optical Engineering, 2011

Many flexible parameterizations exist to represent data on the sphere. In addition to the venerab... more Many flexible parameterizations exist to represent data on the sphere. In addition to the venerable spherical harmonics, we have the Slepian basis, harmonic splines, wavelets and wavelet-like Slepian frames. In this paper we focus on the latter two: spherical wavelets developed for geophysical applications on the cubed sphere, and the Slepian "tree", a new construction that combines a quadratic concentration measure with wavelet-like multiresolution. We discuss the basic features of these mathematical tools, and illustrate their applicability in parameterizing large-scale global geophysical (inverse) problems.

Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 2006

The hyperspectral subpixel detection and classification problem has been intensely studied in the... more The hyperspectral subpixel detection and classification problem has been intensely studied in the downward-looking case, typically satellite imagery of agricultural and urban areas. In contrast, the hyperspectral imaging case when &amp;amp;amp;amp;amp;amp;quot;looking up&amp;amp;amp;amp;amp;amp;quot; at small or distant satellites creates new and unforeseen problems. Usually one pixel or one fraction of a pixel contains the imaging target, and spectra tend to be

Signal Processing, 2013

We analyze the Synchrosqueezing transform, a consistent and invertible time-frequency analysis to... more We analyze the Synchrosqueezing transform, a consistent and invertible time-frequency analysis tool that can identify and extract oscillating components (of time-varying frequency and amplitude) from regularly sampled time series. We first describe a fast algorithm implementing the transform. Second, we

European Signal Processing Conference, 2009

Wavelet transforms and machine learning tools can be used to assist art experts in the stylistic ... more Wavelet transforms and machine learning tools can be used to assist art experts in the stylistic analysis of paintings. A dual-tree complex wavelet transform, Hidden Markov Tree modeling and Random Forest classifiers are used here for a stylistic analysis of Vincent van Gogh's paintings with results on two stylometry challenges that concern “dating, resp. extracting distinguishing features”.