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Estimating Covariances of Locally Stationary Processes: Rates of Convergence of Best Basis Methods
, 1998
"... Mallat, Papanicolaou and Zhang [MPZ98] recently proposed a method for approximating the covariance of a locally stationary process by a covariance which is diagonal in a specially constructed Coifman--Meyer basis of cosine packets. In this paper we extend this approach to estimating the covariance ..."
Abstract
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Cited by 28 (10 self)
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from sampled data. Our method combines both wavelet shrinkage and cosine-packet best-basis selection in a simple and natural way. The resulting algorithm is fast and automatic. The method has an interpretation as a nonlinear, adaptive form of anisotropic timefrequency smoothing. We introduce a new
Entropy-Based Algorithms For Best Basis Selection
- IEEE Transactions on Information Theory
, 1992
"... pretations (position, frequency, and scale), and we have experimented with feature-extraction methods that use best-basis compression for front-end complexity reduction. The method relies heavily on the remarkable orthogonality properties of the new libraries. It is obviously a nonlinear transformat ..."
Abstract
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Cited by 670 (20 self)
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pretations (position, frequency, and scale), and we have experimented with feature-extraction methods that use best-basis compression for front-end complexity reduction. The method relies heavily on the remarkable orthogonality properties of the new libraries. It is obviously a nonlinear
A Complexity Constraint Best-Basis Wavelet Packet Algorithm for Image Compression
"... The concept of adapted waveform analysis using a best basis selection out of a predefined library of wavelet packet (WP) bases allows an efficient representation of a signal. These methods usually have the disadvantage of high computational complexity. In this paper we introduce an extension of the ..."
Abstract
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Cited by 1 (0 self)
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of the best-basis method, the complexity constrained best-basis algorithm (CCBB) which allows an adaptive approach, has relatively low complexity and is memory saving. Our CCBB algorithm generates iteratively a scarce library of WP bases by extending a given library according to the energy distribution
AN ARCHITECTURE DESIGN OF THRESHOLD-BASED BEST-BASIS ALGORITHM
"... The best-basis algorithm has gained much importance on textured-based image compression and denoising of signals. In this paper, an architecture for the wavelet-packet based best-basis algorithm for images is proposed. The paper also describes the architecture for best-tree selection from 2D wavelet ..."
Abstract
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Cited by 1 (0 self)
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The best-basis algorithm has gained much importance on textured-based image compression and denoising of signals. In this paper, an architecture for the wavelet-packet based best-basis algorithm for images is proposed. The paper also describes the architecture for best-tree selection from 2D
Best-Basis Analysis of Broadband Tremor Signals
"... Active volcanos usually generate highly nonstationary broadband tremor signals. Short-time shock events with a frequency content of several decades are superimposed to a stationary narrow band continuous tremor. Tremor signals of this type can be observed in the near field of many active volcanos. I ..."
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. In this paper we will demonstrate the analysis of such signals using a specific tremor signal of Mt. Stromboli (Sicily). We used the Best-Basis Algorithm (BBA) in order to compute a spectrogram which is adapted to signal properties on highly different scales. It turns out that the BBA can reveal better fitting
Ensemble Methods in Machine Learning
- MULTIPLE CLASSIFIER SYSTEMS, LBCS-1857
, 2000
"... Ensemble methods are learning algorithms that construct a set of classifiers and then classify new data points by taking a (weighted) vote of their predictions. The original ensemble method is Bayesian averaging, but more recent algorithms include error-correcting output coding, Bagging, and boostin ..."
Abstract
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Cited by 607 (3 self)
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Ensemble methods are learning algorithms that construct a set of classifiers and then classify new data points by taking a (weighted) vote of their predictions. The original ensemble method is Bayesian averaging, but more recent algorithms include error-correcting output coding, Bagging
The Hungarian method for the assignment problem
- Naval Res. Logist. Quart
, 1955
"... Assuming that numerical scores are available for the performance of each of n persons on each of n jobs, the "assignment problem" is the quest for an assignment of persons to jobs so that the sum of the n scores so obtained is as large as possible. It is shown that ideas latent in the work ..."
Abstract
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Cited by 1238 (0 self)
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in the work of two Hungarian mathematicians may be exploited to yield a new method of solving this problem. 1.
Image registration methods: a survey
- IMAGE AND VISION COMPUTING
, 2003
"... This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align t ..."
Abstract
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Cited by 734 (9 self)
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This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align
An introduction to variational methods for graphical models
- TO APPEAR: M. I. JORDAN, (ED.), LEARNING IN GRAPHICAL MODELS
"... ..."
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