What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Quantum mechanics
His primary scientific interests are in Wavelet, Wavelet transform, Multifractal system, Algorithm and Scaling.
The various areas that Patrice Abry examines in his Wavelet study include Scale, Hurst exponent, Self-similarity, Estimator and Mathematical optimization.
The study incorporates disciplines such as Estimation theory and Fractal in addition to Wavelet transform.
His study in Estimation theory is interdisciplinary in nature, drawing from both Gaussian and Data mining.
Patrice Abry has researched Multifractal system in several fields, including Image processing, Stochastic process, Statistical physics and Bootstrapping.
His study focuses on the intersection of Algorithm and fields such as Calculus with connections in the field of Filter bank.
His most cited work include:
- Wavelet analysis of long-range-dependent traffic (869 citations)
- A wavelet-based joint estimator of the parameters of long-range dependence (457 citations)
- Wavelets for the Analysis, Estimation, and Synthesis of Scaling Data (323 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Wavelet, Multifractal system, Statistical physics, Artificial intelligence and Wavelet transform.
His studies deal with areas such as Fractal, Mathematical analysis, Estimator, Applied mathematics and Algorithm as well as Wavelet.
His Estimator study combines topics from a wide range of disciplines, such as Estimation theory, Covariance and Hurst exponent.
Patrice Abry focuses mostly in the field of Multifractal system, narrowing it down to matters related to Bayes estimator and, in some cases, Bayesian inference.
His Statistical physics study incorporates themes from Stochastic process, Gaussian, Scaling and Combinatorics.
His research investigates the connection between Artificial intelligence and topics such as Pattern recognition that intersect with problems in Signal processing.
He most often published in these fields:
- Wavelet (42.42%)
- Multifractal system (30.91%)
- Statistical physics (22.12%)
What were the highlights of his more recent work (between 2015-2021)?
- Wavelet (42.42%)
- Multifractal system (30.91%)
- Multivariate statistics (8.48%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Wavelet, Multifractal system, Multivariate statistics, Artificial intelligence and Statistical physics.
Patrice Abry works in the field of Wavelet, focusing on Wavelet transform in particular.
His Multifractal system research also works with subjects such as
- Bayes estimator and related Prior probability and Algorithm,
- Heartbeat, which have a strong connection to Nonlinear system, Heart rate variability, Point process and Heart rate.
His Multivariate statistics research is multidisciplinary, incorporating elements of Stochastic process, Bivariate analysis, Monte Carlo method and Hurst exponent.
His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning and Pattern recognition.
His Statistical physics research incorporates themes from Scale, Cumulant, Combinatorics, Gravitational singularity and Scaling.
Between 2015 and 2021, his most popular works were:
- Scaling in Internet Traffic: A 14 Year and 3 Day Longitudinal Study, With Multiscale Analyses and Random Projections (43 citations)
- Sparse Support Vector Machine for Intrapartum Fetal Heart Rate Classification (42 citations)
- Multiscale Analysis of Intensive Longitudinal Biomedical Signals and Its Clinical Applications (38 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Quantum mechanics
Patrice Abry focuses on Wavelet, Multifractal system, Statistical physics, Estimator and Artificial intelligence.
Many of his studies on Wavelet involve topics that are commonly interrelated, such as Image processing.
His work carried out in the field of Multifractal system brings together such families of science as Heart failure, Multivariate statistics, Bayesian probability, Legendre transformation and Calculus.
His Statistical physics study combines topics in areas such as Pointwise, Fractal and Gravitational singularity.
His research integrates issues of Fractional Brownian motion, Matrix and Applied mathematics in his study of Estimator.
His Artificial intelligence research integrates issues from Heart rate variability, Machine learning, Physiological control and Pattern recognition.
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