D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 78 Citations 31,618 777 World Ranking 496 National Ranking 297

Research.com Recognitions

Awards & Achievements

2000 - IEEE Fellow For development of the gamma neural model and for its applications in signal processing.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

Jose C. Principe spends much of his time researching Artificial intelligence, Algorithm, Pattern recognition, Artificial neural network and Entropy. Jose C. Principe has included themes like Machine learning and Signal processing in his Artificial intelligence study. His Algorithm study incorporates themes from Mean squared error, Kernel, Kernel method and Mathematical optimization.

His Pattern recognition study combines topics in areas such as Time delay neural network, Measure, Outlier and Blind signal separation. His Artificial neural network study integrates concerns from other disciplines, such as Control theory and Nonlinear system. His Entropy study combines topics from a wide range of disciplines, such as Information theory, Probability density function and Estimator.

His most cited work include:

  • Correntropy: Properties and Applications in Non-Gaussian Signal Processing (896 citations)
  • Neural and adaptive systems : fundamentals through simulations (791 citations)
  • Information Theoretic Learning (517 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Artificial intelligence, Algorithm, Pattern recognition, Artificial neural network and Machine learning. The study incorporates disciplines such as Electroencephalography, Computer vision and Signal processing in addition to Artificial intelligence. The concepts of his Algorithm study are interwoven with issues in Entropy, Mathematical optimization, Kernel and Nonlinear system.

His studies deal with areas such as Information theory and Estimator as well as Entropy. As part of his studies on Pattern recognition, he often connects relevant subjects like Blind signal separation. His research related to Time delay neural network and Backpropagation might be considered part of Artificial neural network.

He most often published in these fields:

  • Artificial intelligence (44.04%)
  • Algorithm (28.33%)
  • Pattern recognition (24.04%)

What were the highlights of his more recent work (between 2016-2021)?

  • Artificial intelligence (44.04%)
  • Algorithm (28.33%)
  • Pattern recognition (24.04%)

In recent papers he was focusing on the following fields of study:

Jose C. Principe mainly focuses on Artificial intelligence, Algorithm, Pattern recognition, Kernel and Machine learning. His Artificial intelligence study often links to related topics such as Computer vision. His Algorithm research is multidisciplinary, incorporating perspectives in Matrix, Nonlinear system, Entropy, Similarity measure and Robustness.

His Robustness research incorporates elements of Mean squared error, Adaptive filter and Outlier. In his study, Pixel is strongly linked to Image, which falls under the umbrella field of Pattern recognition. His Kernel study deals with Kernel intersecting with Training set and Feature vector.

Between 2016 and 2021, his most popular works were:

  • Maximum Correntropy Kalman Filter (216 citations)
  • Maximum Correntropy Kalman Filter (216 citations)
  • Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation (115 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Machine learning

His scientific interests lie mostly in Artificial intelligence, Algorithm, Information theory, Pattern recognition and Reinforcement learning. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Brain–computer interface and Computer vision. His Algorithm research includes themes of Random variable, Variable kernel density estimation, Kalman filter, Similarity measure and Robustness.

He interconnects Hermitian matrix, Convolutional neural network, Matrix, Mutual information and Perceptron in the investigation of issues within Information theory. His Pattern recognition research integrates issues from Time domain, Signal and Interfacing. Jose C. Principe focuses mostly in the field of Reinforcement learning, narrowing it down to topics relating to Value of information and, in certain cases, Mathematical optimization and Markov process.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Neural and adaptive systems : fundamentals through simulations

J. C. Príncipe;Neil R. Euliano;W. Curt Lefebvre.
(2000)

1879 Citations

Correntropy: Properties and Applications in Non-Gaussian Signal Processing

Weifeng Liu;P.P. Pokharel;J.C. Principe.
IEEE Transactions on Signal Processing (2007)

1143 Citations

Information Theoretic Learning: Renyi's Entropy and Kernel Perspectives

Jose C. Principe.
(2010)

963 Citations

Cooperative Diversity of Spectrum Sensing in Cognitive Radio Networks

Dongliang Duan;Liuqing Yang;Jose C. Principe.
wireless communications and networking conference (2009)

890 Citations

Information Theoretic Learning

Jose C. Principe.
Information Theoretic Learning by Jose C. Principe (2010)

796 Citations

Kernel Adaptive Filtering: A Comprehensive Introduction

Weifeng Liu;Jose C. Principe;Simon Haykin.
(2010)

754 Citations

Adaptive and Learning Systems for Signal Processing, Communication, and Control

Weifeng Liu;José C. Príncipe;Simon Haykin.
(2010)

653 Citations

Support vector machines for SAR automatic target recognition

Q. Zhao;J.C. Principe.
IEEE Transactions on Aerospace and Electronic Systems (2001)

600 Citations

The Kernel Least-Mean-Square Algorithm

Weifeng Liu;P.P. Pokharel;J.C. Principe.
IEEE Transactions on Signal Processing (2008)

561 Citations

Adaptive epileptic seizure prediction system

L.D. Iasemidis;Deng-Shan Shiau;W. Chaovalitwongse;J.C. Sackellares.
IEEE Transactions on Biomedical Engineering (2003)

481 Citations

Best Scientists Citing Jose C. Principe

Badong Chen

Badong Chen

Xi'an Jiaotong University

Publications: 146

Plamen Angelov

Plamen Angelov

Lancaster University

Publications: 57

Deniz Erdogmus

Deniz Erdogmus

Northeastern University

Publications: 55

Haiquan Zhao

Haiquan Zhao

Southwest Jiaotong University

Publications: 40

Danilo P. Mandic

Danilo P. Mandic

Imperial College London

Publications: 39

Walter J. Freeman

Walter J. Freeman

University of California, Berkeley

Publications: 38

Mikhail A. Lebedev

Mikhail A. Lebedev

Skolkovo Institute of Science and Technology

Publications: 36

Bao-Gang Hu

Bao-Gang Hu

Chinese Academy of Sciences

Publications: 35

Ran He

Ran He

Chinese Academy of Sciences

Publications: 34

Thomas Villmann

Thomas Villmann

Hochschule Mittweida

Publications: 33

Panos M. Pardalos

Panos M. Pardalos

University of Florida

Publications: 33

Miguel A. L. Nicolelis

Miguel A. L. Nicolelis

Duke University

Publications: 32

Francesco Carlo Morabito

Francesco Carlo Morabito

University of Reggio Calabria

Publications: 30

Andrzej Cichocki

Andrzej Cichocki

Skolkovo Institute of Science and Technology

Publications: 29

Ram Bilas Pachori

Ram Bilas Pachori

Indian Institute of Technology Indore

Publications: 28

Sergios Theodoridis

Sergios Theodoridis

National and Kapodistrian University of Athens

Publications: 28

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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