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)
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 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.
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.
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.
Adaptive Signal Processing
Bernard Widrow;Samuel D. Stearns.
Adaptive noise cancelling: Principles and applications
B. Widrow;J.R. Glover;J.M. McCool;J. Kaunitz.
Proceedings of the IEEE (1975)
Adaptive switching circuits
Bernard Widrow;Marcian E. Hoff.
Neurocomputing: foundations of research (1988)
30 years of adaptive neural networks: perceptron, Madaline, and backpropagation
B. Widrow;M.A. Lehr.
Proceedings of the IEEE (1990)
Adaptive antenna systems
B. Widrow;P. Mantey;L. Griffiths;B. Goode.
Proceedings of the IEEE (1967)
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)
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)
Neural networks for self-learning control systems
Derrick H. Nguyen;Bernard Widrow.
IEEE Control Systems Magazine (1990)
The complex LMS algorithm
B. Widrow;J. McCool;M. Ball.
Proceedings of the IEEE (1975)
Adaptive inverse control
B. Widrow;M. Bilello.
international symposium on intelligent control (1993)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: