Bernard Widrow | |
|---|---|
 Widrow demonstrating the "Knobby Adaline" device (1963) | |
| Born | December 24, 1929 |
| Nationality | American |
| Alma mater | Massachusetts Institute of Technology[1] |
| Scientific career | |
| Fields | Electrical engineering |
| Institutions | Stanford University |
| Doctoral advisor | William Linvill |
| Doctoral students | |
Bernard Widrow (born December 24, 1929) is a U.S. professor of electrical engineering at Stanford University.[1] He is the co-inventor of the Widrow–Hoff least mean squares filter (LMS) adaptive algorithm with his then doctoral student Ted Hoff.[2] The LMS algorithm led to the ADALINE and MADALINE artificial neural networks and to the backpropagation technique. He made other fundamental contributions to the development of signal processing in the fields of geophysics, adaptive antennas, and adaptive filtering. A summary of his work is.[3]
He is the namesake of "Uncle Bernie's Rule": the training sample size should be 10 times the number of weights in a network.[4][5]
- ^ a b "Widrow's Stanford web page". Information Systems Laboratory, Electrical Engineering Department, Stanford University.
- ^ Andrew Goldstein (1997). "Bernard Widrow Oral History". IEEE Global History Network. IEEE. Retrieved 22 August 2011.
- ^ Widrow, B.; Lehr, M.A. (September 1990). "30 years of adaptive neural networks: perceptron, Madaline, and backpropagation". Proceedings of the IEEE. 78 (9): 1415–1442. doi:10.1109/5.58323.
- ^ Morgan, N.; Bourlard, H. (1989). "Generalization and Parameter Estimation in Feedforward Nets: Some Experiments". Advances in Neural Information Processing Systems. 2. Morgan-Kaufmann.
- ^ "(1960) Bernard Widrow and Marcian E. Hoff, "Adaptive switching circuits," [i]1960 IRE WESCON Convention Record[/i], New York: IRE, pp. 96-104.", Neurocomputing, Volume 1, The MIT Press, pp. 123–134, 1988-04-07, doi:10.7551/mitpress/4943.003.0012, ISBN 9780262267137, retrieved 2023-11-03