H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 46 Citations 40,335 90 World Ranking 1405 National Ranking 635

Research.com Recognitions

Awards & Achievements

2001 - Benjamin Franklin Medal, Franklin Institute

1995 - Member of the National Academy of Engineering For contributions to the theory of quantization noise, adaptive signal processing, and neural networks.

1991 - Neural Networks Pioneer Award, IEEE Computational Intelligence Society

1986 - IEEE Alexander Graham Bell Medal "For fundamental contributions to adaptive filtering, adaptive noise and echo cancellation, and adaptive antennas."

1980 - Fellow of the American Association for the Advancement of Science (AAAS)


What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Electrical engineering
  • Machine learning

Bernard Widrow mostly deals with Control theory, Adaptive filter, Artificial intelligence, Artificial neural network and Algorithm. His Control theory research incorporates elements of Directivity, Main lobe, Filter and Noise. His research in Adaptive filter is mostly focused on Least mean squares filter.

Within one scientific family, Bernard Widrow focuses on topics pertaining to Nonlinear system under Artificial neural network, and may sometimes address concerns connected to Piecewise linear function and Control engineering. His study in Algorithm is interdisciplinary in nature, drawing from both Multidelay block frequency domain adaptive filter and Adaptive system. Bernard Widrow has researched Adaptive beamformer in several fields, including Antenna array and Adaptive control.

His most cited work include:

  • Adaptive Signal Processing (5368 citations)
  • Adaptive noise cancelling: Principles and applications (3725 citations)
  • Adaptive switching circuits (3097 citations)

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

His main research concerns Control theory, Adaptive filter, Artificial neural network, Algorithm and Artificial intelligence. The various areas that Bernard Widrow examines in his Control theory study include Control engineering and Signal. Bernard Widrow works mostly in the field of Adaptive filter, limiting it down to topics relating to Signal processing and, in certain cases, Active noise control.

His Artificial neural network research incorporates elements of Nonlinear control and Nonlinear system. As part of his studies on Algorithm, Bernard Widrow often connects relevant subjects like Multidelay block frequency domain adaptive filter. His Artificial intelligence study incorporates themes from Machine learning, Computer vision and Pattern recognition.

He most often published in these fields:

  • Control theory (31.88%)
  • Adaptive filter (23.19%)
  • Artificial neural network (21.26%)

What were the highlights of his more recent work (between 2003-2018)?

  • Algorithm (19.81%)
  • Quantization (11.11%)
  • Artificial intelligence (19.32%)

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

Bernard Widrow mainly investigates Algorithm, Quantization, Artificial intelligence, Control theory and Electronic engineering. His primary area of study in Algorithm is in the field of Least mean squares filter. His Least mean squares filter study is associated with Adaptive filter.

His studies in Artificial intelligence integrate themes in fields like Machine learning and Computer vision. Bernard Widrow focuses mostly in the field of Control theory, narrowing it down to matters related to Control engineering and, in some cases, Disturbance. He has included themes like Acoustics, Roundoff noise and Noise in his Electronic engineering study.

Between 2003 and 2018, his most popular works were:

  • Quantization Noise: Quantization of System Parameters (202 citations)
  • Quantization Noise: Roundoff Error in Digital Computation, Signal Processing, Control, and Communications (173 citations)
  • Least-Mean-Square Adaptive Filters: Haykin/Least-Mean-Square Adaptive Filters (162 citations)

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

  • Artificial intelligence
  • Electrical engineering
  • Machine learning

His primary scientific interests are in Artificial intelligence, Algorithm, Adaptive filter, Artificial neural network and Least mean squares filter. His research integrates issues of Machine learning and Cognitive computing in his study of Artificial intelligence. He is investigating Adaptive filter as part of his inquiry into Control theory and Electronic engineering.

He works mostly in the field of Control theory, limiting it down to concerns involving Radiation and, occasionally, Nonlinear system. His Backpropagation study in the realm of Artificial neural network interacts with subjects such as Facial recognition system. His Least mean squares filter research includes themes of Mean squared error, Mathematical optimization, Adaptive algorithm and Recursive least squares filter.

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

Adaptive Signal Processing

Bernard Widrow;Samuel D. Stearns.

11334 Citations

Adaptive noise cancelling: Principles and applications

B. Widrow;J.R. Glover;J.M. McCool;J. Kaunitz.
Proceedings of the IEEE (1975)

6270 Citations

Adaptive switching circuits

Bernard Widrow;Marcian E. Hoff.
Neurocomputing: foundations of research (1988)

5028 Citations

30 years of adaptive neural networks: perceptron, Madaline, and backpropagation

B. Widrow;M.A. Lehr.
Proceedings of the IEEE (1990)

3039 Citations

Adaptive antenna systems

B. Widrow;P. Mantey;L. Griffiths;B. Goode.
Proceedings of the IEEE (1967)

1978 Citations

Stationary and nonstationary learning characteristics of the LMS adaptive filter

B. Widrow;J.M. McCool;M.G. Larimore;C.R. Johnson.
Proceedings of the IEEE (1976)

1955 Citations

Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights

D. Nguyen;B. Widrow.
international joint conference on neural network (1990)

1795 Citations

Neural networks for self-learning control systems

Derrick H. Nguyen;Bernard Widrow.
IEEE Control Systems Magazine (1990)

1213 Citations

The complex LMS algorithm

B. Widrow;J. McCool;M. Ball.
Proceedings of the IEEE (1975)

925 Citations

Adaptive inverse control

B. Widrow;M. Bilello.
international symposium on intelligent control (1993)

923 Citations

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