Don H. Johnson

J.S. Abercrombie Professor, Departments of Electrical and Computer Engineering and of Statistics
Rice University

Electrical & Computer Engineering Department, MS380
Rice University
Houston, Texas 77005-1892

Office: (713) 348-4956
FAX: (713) 348-5685
dhj@rice.edu

S.B.,S.M.(1970), E.E.(1971), Ph.D.(1974), Electrical Engineering, MIT

Research Interests

Statistical signal processing; theoretical neuroscience

Awards & Honors

IEEE Signal Processing Society Meritorious Service Award (2001)
IEEE Millenium Medal (2000)
IEEE Signal Processing Society Distinguished Lecturer, 2000-01
Tau Beta Pi, Eta Kappa Nu
Fellow, IEEE (1990)
George R. Brown Award for Excellence in Teaching (1988)
George R. Brown Award for Superior Teaching (1982,1985,1986,1995)
Nicolas Salgo Distinguished Teacher Award (1983)
American Society for Engineering Education Fellowship (1980)
Supervised Investors' Award for Teaching (1970)

Educational and Research Highlights

Unreviewed Manscripts and Talks

  1. D.H. Johnson. The Correlation Function of Multiple Dependent Poisson Processes Generated by the Alternating Renewal Process Method. 2007.
  2. D.H. Johnson. Correlations in Populations: Information-Theoretic Limits. Cosyne Workshop of Population Correlations. February 2007.
  3. C.J. Rozell, D.H. Johnson, R.G. Baraniuk, B.A. Oldshausen. Locally competitive algorithms for sparse approximation. ICIP, September 2007.
  4. D.H. Johnson. Dialogue Concerning Neural Coding and Information Theory. August 2003.
  5. D.H. Johnson. From Signal to Information Processing. Presentation.
  6. D.H. Johnson. Information processing performance limits of neural populations. Neural Coding Workshop, Mathematical Biosciences Institute, Ohio State University, February 10-14, 2003.
  7. A.G. Dabak and D.H. Johnson. Relations between Kullback-Leibler distance and Fisher information.
  8. D.H. Johnson and S. Sinanovic. Symmetrizing the Kullback-Leibler Distance.

Books

Recent Reviewed Publications

  1. I.N. Goodman and D.H. Johnson. Information theoretic bounds on neural prosthesis effectiveness: The importance of spike sorting. ICASSP'08.
  2. M.A. Lexa and D.H. Johnson. Distributed Structures, Sequential Optimization, and Quantization for Detection. IEEE Trans. Signal Processing, 56: 1740–1745, 2008.
  3. D.H. Johnson and I.N. Goodman. Inferring the Capacity of the Vector Poisson Channel with a Bernoulli Model. Network: Computation in Neural Systems, 19: 13–33, 2008.
  4. M. Sheikh and D.H. Johnson. Fundamental Detection and Estimation Limits in Spike Sorting. ICASSP'07.
  5. M.A. Lexa and D.H. Johnson. Joint optimization of distributed broadcast quantization systems for classification. DCC'07.
  6. S. Sinanovic and D.H. Johnson. Toward a theory of information processing. Signal Processing, 87: 1326–1344, 2007.
  7. Don H. Johnson Signal-to-noise ratio. Scholarpedia, 1(12):2088, 2006.
  8. J. Uppuluri and D.H. Johnson. Detecting correlated population responses.CNS'06.
  9. M.A. Sheikh and D.H. Johnson. Favorable recording criteria for spike sorting. CNS'06.
  10. C.J. Rozell and D.H. Johnson. Evaluating local contributions to global performance in wireless sensor and actuator networks. DCOSS'06.
  11. S. Sinanovic, D.H. Johnson, W. Gardner. Directional propagation cancellation for acoustic communication along the drill string. ICASSP'06.
  12. C.J. Rozell, I. Goodman and D.H. Johnson. Feature-based information processing with selective attention. ICASSP'06.
  13. M. Memarzadeh, D.H. Johnson, W. Gardner, L. Gao. On maximizing the fidelity of log signals transmitted via digital telemetry. Society of Petroleum Engineers, 2006.
  14. C.J. Rozell and D.H. Johnson. Analyzing the robustness of redundant population codes in sensory and feature extraction systems. CNS'05.
  15. C.J. Rozell and D.H. Johnson. Analysis of noise reduction in redundant expansions under distributed processing requirements. ICASSP'05.
  16. D.H. Johnson and J. Uppuluri. Finding likely models that describe population responses. CNS'04.
  17. C. Rozell and D.H. Johnson. Examining methods for estimating mutual information in spiking neural systems. CNS'04.
  18. D.H. Johnson and R.M. Glantz. When does interval coding occur? Neurocomputing, 59–60:13–18, 2004.
  19. C. Rozell, D.H. Johnson and R.M. Glantz. Measuring information transfer in crayfish sustaining fiber spike generators: Methods and analysis. J. Biol. Cybernetics, 90:89–97, 2004.
  20. D.H. Johnson. Neural population structures and consequences for neural coding. J. Computational Neuroscience, 16: 69–80, 2004.
  21. D.H. Johnson and W. Ray. Optimal stimulus coding by neural populations using rate codes. J. Computational Neuroscience, 16: 129–138, 2004.
  22. A.M. Lexa and D.H. Johnson. An information processing approach to distributed detection. Workshop on Statistical Signal Processing, Sept. 2003.
  23. I. Goodman and D.H. Johnson. New multivariate dependence measures and applications to neural ensembles. Workshop on Statistical Signal Processing, Sept. 2003.
  24. A.M. Lexa and D.H. Johnson. Optimizing binary decision systems by manipulating transmission intervals. International Symposium on Signal Processing and its Applications, July 2003.
  25. C.S. Miller, D.H. Johnson, J.P. Schroeter, L. Myint and R.M. Glantz. Visual responses of crayfish ocular motoneurons: An information theoretical analysis. J. Computational Neuroscience, 15: 247–269, 2003.
  26. D.H. Johnson. Origins of the Equivalent Circuit Concept: The Voltage-Source Equivalent. Proc. IEEE, 91: 636–640, 2003.
  27. D.H. Johnson. Origins of the Equivalent Circuit Concept: The Current-Source Equivalent. Proc. IEEE, 91: 817–821, 2003.
  28. A.M. Lexa and D.H. Johnson. A new look at the informational gain of soft decisions. ICASSP, 2003.
  29. D.H. Johnson and H. Rodriguez-Diaz. Optimizing physical layer data transmission for minimal signal distortion. ICASSP, 2003.
  30. M.A. Lexa and D.H. Johnson. Information processing of linear block decoders. DSP Workshop, 2002.
  31. C.S. Miller, D.H. Johnson, J.P. Schroeter, L.L. Myint, and R.M. Glantz. Visual signal in an optomotor reflex: Systems and information theoretic analysis. J. Computational Neuroscience, 13: 5–21, July/August 2002.
  32. C. Rozell and D.H. Johnson. Information processing during transient responses in the crayfish visual system. CNS*02, July 2002 and Neurocomputing, 2003.
  33. D.H. Johnson. Four top reasons why mutual information does not assess neural information processing. CNS*02, July 2002.
  34. W. Wang and D.H. Johnson. Linear transforms of symbolic data. IEEE Trans. Signal Processing, 10: 628–634, March, 2002.
  35. D.H. Johnson, C.M. Gruner, K. Baggerly, and C. Seshagiri. Information-theoretic analysis of neural coding. J. Computational Neuroscience, 10: 47–69, 2001.
  36. D.H. Johnson, C.M. Gruner, and R.M. Glantz. Quantifying information transfer in spike generation. Neurocomputing, 33: 1047–1054, 2000.
  37. S. Sinanovic and D.H. Johnson. Toward a theory of information processing. International Symposium on Information Theory, 2000.
  38. D.H. Johnson and J.D. Wise, Jr. A different first course in electrical engineering.Signal Processing Magazine, 16: 34–37, September 1999.
  39. C.M. Gruner and D.H. Johnson. Correlation and neural information coding fidelity and efficiency. Neurocomputing, 26-27: 163–168, 1999.
  40. M. Zacksenhouse, D. H. Johnson, J. Williams, and C. Tsuchitani. Single-neuron modeling of LSO unit responses. J. Neurophysiol. 75: 3098–3110, June 1998.
  41. L. Yue and D.H. Johnson. Optimal binaural processing based on point process models of preprocessed cues. J. Acoust. Soc. Am. 101: 982–992, Feb 1997.
  42. C.C. Leang and D.H. Johnson. On the asymptotics of M-hypothesis Bayesian detection. IEEE Trans. Info. Th. 43: 280–282, Jan 1997.
  43. D.H. Johnson. Optimal linear detectors for additive noise channels. IEEE Trans. Signal Processing 44: 3079–3084, Dec 1996.
  44. D.H. Johnson. Point process models of single-neuron discharges. J. Computational Neuroscience 3: 275–299, 1996.
  45. O.E. Kelly, D.H. Johnson, B. Delgutte, and P. Cariani. Fractal noise strength in auditory-nerve fiber recordings. J. Acoust. Soc. Am. 99: 2210–2220, April 1996.

Papers Selected for Special Recognition

4/5/08