Don H. Johnson

J.S. Abercrombie Professor Emeritus, Department of Electrical and Computer Engineering
Rice University

Electrical & Computer Engineering Department, MS366
Rice University
6100 Main Street
Houston, Texas 77005

Office: (713) 348-4956
FAX: (713) 348-5686
dhj@rice.edu

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

Research Interests

Statistical signal processing; image processing in art

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 and I.N. Goodman. Jointly Poisson Processes. 2009.
  2. D.H. Johnson. The Correlation Function of Multiple Dependent Poisson Processes Generated by the Alternating Renewal Process Method. 2007.
  3. D.H. Johnson. Correlations in Populations: Information-Theoretic Limits. Cosyne Workshop of Population Correlations. February 2007.
  4. D.H. Johnson. From Signal to Information Processing. Presentation.
  5. D.H. Johnson. Information processing performance limits of neural populations. Neural Coding Workshop, Mathematical Biosciences Institute, Ohio State University, February 10-14, 2003.
  6. A.G. Dabak and D.H. Johnson. Relations between Kullback-Leibler distance and Fisher information.
  7. D.H. Johnson and S. Sinanovic. Symmetrizing the Kullback-Leibler Distance.

Books and Book Chapters

  1. D.H. Johnson, C.R. Johnson, Jr., E. Hendriks. Automated thread counting. Chapter 8 in van Gogh's Studio Practice, edited by M. Vellekoop, M. Geldof, E.Hendriks, L. Jansen and A. de Tagle, Mercatorfonds, 2013, pp. 142–155.
  2. E. Hendriks, C.R. Johnson, Jr., D.H. Johnson, M. Geldof. Automated thread counting and the Studio Practice Project. Chapter 9 in van Gogh's Studio Practice, edited by M. Vellekoop, M. Geldof, E.Hendriks, L. Jansen and A. de Tagle, Mercatorfonds, 2013, pp. 156–181.
  3. J. Salvant, M. Geldof, E. Ravaud, L. Megens, C. Walbert, M. Menu, D.H. Johnson. Investigation of the grounds of Tasset et L'Hôte commercially primed canvases used by Vincent van Gogh in the period 1888 to 1890. Chapter 10 in van Gogh's Studio Practice, edited by M. Vellekoop, M. Geldof, E.Hendriks, L. Jansen and A. de Tagle, Mercatorfonds, 2013, pp. 182–201.
  4. D.H. Johnson. Principles of neural signal processing. Chapter 4 in Biohybrid Systems edited by Ranu Jung, 53–75. Wiley-VCH, 2011.
  5. D.H. Johnson. Information-theoretic analysis of neural data. Chapter 3 in Statistical Signal Processing for Neuroscience and Neurotechnology edited by Karim Oweiss, 69–92, Elsevier, 2010.
  6. D.H. Johnson, C.J. Rozell, I.N. Goodman. Information theory and systems neuroscience. Chapter 13 in Analysis of Parallel Spike Trains edited by Sonja Grün. Springer, 2010.
  7. D.H. Johnson. Fundamentals of Electrical Engineering I, The Connexions Project, 2005.
  8. D.H. Johnson and D.E. Dudgeon. Array Signal Processing: Concepts and Techniques, Prentice-Hall, 1993.

Recent Reviewed Publications

  1. C.R. Johnson, Jr., D.H. Johnson, I. Verslype, R. Lugtigheid, R.G. Erdmann. Detecting weft snakes. Art Matters, 5: 48–52, 2013.
  2. D.H. Johnson, E. Hendriks, C.R. Johnson, Jr. Interpreting canvas weave matches. Art Matters, 5: 53–61, 2013.
  3. D.H. Johnson, C.R. Johnson, Jr., R.G. Erdmann. Weave analysis of paintings on canvas from radiographs. Signal Processing, 93: 527–540, 2013.
  4. W. Liedtke, C.R. Johnson, Jr., D.H. Johnson. Canvas matches in Vermeer: A case study in the fabric analysis of canvas supports. Metropolitan Museum Journal, 47: 101108, 2012.
  5. P. Pérez d’Ors, C.R. Johnson, Jr., D.H. Johnson. Velázquez in Fraga: A new hypothesis about the portraits of El Primo and Philip IV. Burlington Magazine, 154: 620625, 2012.
  6. E. Hendriks, D.H. Johnson and C.R. Johnson, Jr. Interpreting canvas weave matches. Art Matters, 2012.
  7. L. van~Tilborgh, T. Meedendorp, E. Hendriks, D.H. Johnson, C.R. Johnson, Jr. Weave matching and dating of van Gogh’s paintings: an interdisciplinary approach. Burlington Magazine, 154: 112–122, 2012.
  8. C.R. Johnson, Jr., D.H. Johnson, N. Hamashima, H.S. Yang, E. Hendriks. On the utility of spectral-maximum-based automated thread counting from X-rays of paintings on canvas. Studies in Conservation, 156: 104–114, 2012.
  9. P. Noble, A. van Loon, C.R. Johnson, Jr. and D.H. Johnson. Technical investigation of Rembrandt and/or studio of Saul and David, c. 1660, from the collection of the Mauritshaus. ICOM-CC, Lisbon, 2011.
  10. D.H. Johnson. Information theory and neural information processing. IEEE Trans. Information Theory, 56: 653–666, 2010.
  11. D.H. Johnson, C.R. Johnson, Jr. and E. Hendriks. Signal processing and analyzing works of art. SPIE'10.
  12. D.H Johnson, E. Hendriks, M. Geldof and C.R. Johnson, Jr.. Do weave matches imply canvas roll matches? AIC'10.
  13. D.H. Johnson, C.R. Johnson, Jr. and E. Hendriks. Matching canvas weave patterns from processing x-ray images of master paintings. ICASSP'10.
  14. D.H. Johnson and C.R. Johnson, Jr. A thread counting algorithm for art forensics. DSP Workshop, 2009.
  15. C.J. Rozell, D.H. Johnson, R.G. Baraniuk,B.A. Olshausen. Sparse Coding via Thresholding and Local Competition in Neural Circuits. Neural Computation, 20: 2526–2563, 2008.
  16. I.N. Goodman and D.H. Johnson. Information theoretic bounds on neural prosthesis effectiveness: The importance of spike sorting. ICASSP'08.
  17. M.A. Lexa and D.H. Johnson. Distributed Structures, Sequential Optimization, and Quantization for Detection. IEEE Trans. Signal Processing, 56: 1740–1745, 2008.
  18. 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.
  19. M. Sheikh and D.H. Johnson. Fundamental Detection and Estimation Limits in Spike Sorting. ICASSP'07.
  20. M.A. Lexa and D.H. Johnson. Joint optimization of distributed broadcast quantization systems for classification. DCC'07.
  21. S. Sinanovic and D.H. Johnson. Toward a theory of information processing. Signal Processing, 87: 1326–1344, 2007.
  22. Don H. Johnson Signal-to-noise ratio. Scholarpedia, 1(12):2088, 2006.
  23. J. Uppuluri and D.H. Johnson. Detecting correlated population responses.CNS'06.
  24. M.A. Sheikh and D.H. Johnson. Favorable recording criteria for spike sorting. CNS'06.
  25. C.J. Rozell and D.H. Johnson. Evaluating local contributions to global performance in wireless sensor and actuator networks. DCOSS'06.
  26. S. Sinanovic, D.H. Johnson, W. Gardner. Directional propagation cancellation for acoustic communication along the drill string. ICASSP'06.
  27. C.J. Rozell, I. Goodman and D.H. Johnson. Feature-based information processing with selective attention. ICASSP'06.
  28. 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.
  29. C.J. Rozell and D.H. Johnson. Analyzing the robustness of redundant population codes in sensory and feature extraction systems. CNS'05.
  30. C.J. Rozell and D.H. Johnson. Analysis of noise reduction in redundant expansions under distributed processing requirements. ICASSP'05.
  31. D.H. Johnson and J. Uppuluri. Finding likely models that describe population responses. CNS'04.
  32. C. Rozell and D.H. Johnson. Examining methods for estimating mutual information in spiking neural systems. CNS'04.
  33. D.H. Johnson and R.M. Glantz. When does interval coding occur? Neurocomputing, 59–60:13–18, 2004.
  34. 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.
  35. D.H. Johnson. Neural population structures and consequences for neural coding. J. Computational Neuroscience, 16: 69–80, 2004.
  36. D.H. Johnson and W. Ray. Optimal stimulus coding by neural populations using rate codes. J. Computational Neuroscience, 16: 129–138, 2004.
  37. M.A. Lexa and D.H. Johnson. An information processing approach to distributed detection. Workshop on Statistical Signal Processing, Sept. 2003.
  38. I. Goodman and D.H. Johnson. New multivariate dependence measures and applications to neural ensembles. Workshop on Statistical Signal Processing, Sept. 2003.
  39. M.A. Lexa and D.H. Johnson. Optimizing binary decision systems by manipulating transmission intervals. International Symposium on Signal Processing and its Applications, July 2003.
  40. 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.
  41. D.H. Johnson. Origins of the Equivalent Circuit Concept: The Voltage-Source Equivalent. Proc. IEEE, 91: 636–640, 2003.
  42. D.H. Johnson. Origins of the Equivalent Circuit Concept: The Current-Source Equivalent. Proc. IEEE, 91: 817–821, 2003.
  43. M.A. Lexa and D.H. Johnson. A new look at the informational gain of soft decisions. ICASSP, 2003.
  44. D.H. Johnson and H. Rodriguez-Diaz. Optimizing physical layer data transmission for minimal signal distortion. ICASSP, 2003.
  45. M.A. Lexa and D.H. Johnson. Information processing of linear block decoders. DSP Workshop, 2002.
  46. 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.
  47. C. Rozell and D.H. Johnson. Information processing during transient responses in the crayfish visual system. CNS*02, July 2002 and Neurocomputing, 2003.
  48. D.H. Johnson. Four top reasons why mutual information does not assess neural information processing. CNS*02, July 2002.
  49. W. Wang and D.H. Johnson. Linear transforms of symbolic data. IEEE Trans. Signal Processing, 10: 628–634, March, 2002.

Papers Selected for Special Recognition


8/25/13