Signal and Image Processing
University of Washington
Seattle, WA 98195
| Phone: (206) 685-1315
Stanford University 1984 Ph.D.
Stanford University 1979 M.S.
University of Wisconsin 1977 BSEE
- National Science Foundation Presidential Young Investigator Award, 1985
- Physio-Control Career Development Award, 1984-87
- University of Washington, College of Engineering Nominee for NSF Waterman Prize, 1987
- General Chairman, IEEE International Symposium on Time-Frequency and Time-Scale Analysis, Victoria, BC, October 1992
- Keynote Speaker for Phillips Doppler Ultrasound Conference, 1991
- General Chairman, 1st IEEE International Symposium on Time-Frequency and Time-Scale Analysis, 1992
- General Chairman, IEEE International Conference on Acoustics, Speech, and Signal Processing, Seattle, WA, May 1998
- Board of Governors, IEEE Signal Processing Society, 2000
- Fulbright Senior Research Award for Study in Germany, 2003
- IEEE Fellow, 2004
Theory of Time-Frequency and Time-Scale Analysis: Almost all physical signals come from systems that are time-varying. Our theory drops all the typical assumptions of stationary increments in time (and space) and is able to directly resolve spectral detail while preserving time dynamics. This theory has been extended to develop optimal time-frequency smoothers for classification and detection applications. Current work is directed toward providing a theoretical foundation for spectral analysis and transformations of the dynamics of time-varying systems. This theory has been applied to sonar, radar, machine and manufacturing monitoring, and speech and music signal analysis.
Biomimetic Acoustic Analysis: An interdisciplinary team of researchers from the University of Maryland, Boston University and the University of Washington are providing new principals for acoustic analysis. Prof. Atlas has provided this team with a new framework for understanding how auditory systems represent signals which are time-varying. This new approach, called "autoambiguity analysis," has improved the performance of systems used in manufacturing, machine monitoring, and sonar applications.
Speech Recognition and Analysis: Most researchers agree that most of the information in speech is contained within the time-varying portions of speech. The above time-varying analysis algorithms have been used to determine which aspect of the dynamics is most important for accurate speech recognition and these results have been used to improve recognizer performance.
Interactive Systems Design Lab: https://sites.google.com/a/uw.edu/isdl/
Zhao, Y., L.E. Atlas and R.J. Marks, "The Use of Cone-Shaped Kernels for Generalized Time-Frequency Representations of Nonstationary Signals," IEEE Transactions on Acoustics, Speech and Signal Processing, Vol. 38, No. 7, pp. 1084-1091, July 1990.
Atlas, L., R. Cole, Y. Muthusamy, A. Lippman, J. Connor, D. Park, M. El-Sharkawi, and R.J. Marks II, "A performance comparison of trained multilayer perceptrons and trained classification trees," Proceedings of the IEEE, Vol. 78, pp. 1614-16 19, Oct. 1990.
Zhao, Y., L.E. Atlas, X. Zhaung, "Application of the Gibbs distribution to hidden Markov modeling in speaker independent isolated speech recognition," IEEE Trans. Sig. Proc., Vol. 39, pp. 1291-1299, June 1991.
Loughlin, P.J., J.W. Pitton, and L.E. Atlas, "Construction of Positive Time-Frequency Distributions," IEEE Trans. Sig. Proc., Vol. 42, No. 10, pp. 2697-2705, October 1994.
Pitton, J., L. Atlas, and P. Loughlin, "Positive Time-Frequency Distributions with Application to Speech Processing," IEEE Trans. on Speech and Audio Proc., Vol. 2, No. 4, pp. 554-566, October 1994. (Invited)
Atlas, L., G. D. Bernard and S. B. Narayanan, "Applications of Time-Frequency Analysis to Manufacturing Sensor Signals," Proceedings of the IEEE, Vol. 84, No. 9, pp. 1319- 1329, September 1996. (Invited)
Owsley,L., L. Atlas, and G. Bernard, "Self-organizing feature maps and hidden Markov models for machine-tool monitoring," IEEE Transactions on Signal Processing, vol. 45, pp. 2787-98, November 1997.
Atlas, L., P. Duhamel, "Recent Developments in the Core of Diogital Signal Processing," IEEE Signal Processing Magazine, pp. 16-19, January, 1999.
B. Gillespie and L. Atlas, "Optimization of Time and Frequency Resolution for Radar Transmitter Identification," in Proceedings of the 1999 IEEE ICASSP, vol. 3, pp. 1341-4, 1999.
Gillespie, B.W. and L.E. Atlas, "Optimizing Time-Frequency Kernels for Classification," IEEE Transactions on Signal Processing, pp. 1341-4, March, 2001.
Atlas, L., and S. Shamma, "Joint Acoustic and Modulation Frequency," EURASIP JASP, 2003.
Recent Conference Papers
Owsley, L., L. Atlas, and G. D. Bernard, Automatic Clustering of Vector Time-Series for Manufacturing Machine Monitoring, Proceedings of ICASSP 97, Munich, Germany, April, 1997.
Atlas, L., J. Droppo, and J. McLaughlin, "Optimizing Time-Frequency Distributions for Automatic Classification," Proceedings of SPIE The International Society for Optical Engineering, Vol. 3162, San Diego, CA, pp. 161-171, July, 1997.
Gillespie, B. and L. Atlas, "Data-driven optimization of time and frequency resolution for radar transmitter identification," in Proceedings of the SPIE The International Society for Optical Engineering, vol. 3162, San Diego, CA, July, 1998.
Droppo, J. and L. Atlas, "Application of classifier-optimal time-frequency distributions to to speech analysis," Proceedings IEEE-SP International Symposium on Time-Frequency Time-Scale Analysis, Pittsburgh, PA, pp. 585-588, October, 1998.
Gillespie, B.W. and L. Atlas, "Optimization of Time and Frequency Resolution for Radar Transmitter Identification," Proceedings of ICASSP '99, Phoenix, AZ, March, 1999.
Optical Neural Network Memory, U.S. Patent No. 4,849,940, July 18, 1989, (with R. Marks II and S. Oh).
A Range-Doppler Representation for Sonar and Radar Using CK-GTFRs, Washington Technology Center, Patent Disclosure, May 31, 1990.
A Precise and Noise Insensitive Technique for Tracking Unknown Instantaneous Frequencies, Washington Technology Center, Patent Disclosure, May 31, 1990.
Modulation Freqency, Office of Naval Research, 1/01/02-12/31/05
Auditory Testing, Office of Naval Research, 6/18/03-6/17/06
Modulation Spectra, Army Research Lab, 8/2/03-8/27/06
Current and Recent Graduate Students
Travis Wilkins, M.S.E.E. student.
Scott Phillips, Ph.D., post quals.
Steve Schimmel, Ph.D., post quals.
Qin Li, Ph.D., post quals.
Brad Gillespie, Ph.D., December 2003.
Somsak Sukkittanon, Ph.D., June 2004.
John Keane, Ph.D., December 2004.
Chair, IEEE Signal Processing Society Technical Committee on Signal Processing Theory and Methods, 1998-2000.
Member-at-Large, IEEE Signal Processing Society Board of Governors, 2000-2002.
Member, University of Washington Graduate School Council.
Chair, University of Washington, Department of Electrical Engineering Computing Committee.