Journals and book chapters

  1. D. Gareau, R. Hennessy, E. Wan, G. Pellacani, S. L. Jacques.Automated detection of malignant features in confocal microscopy on superficial spreading melanoma versus nevi. Journal of Biomedical Optics 15(6), 061713 (November/December 2010)
  2. S. Paul and E. A. Wan.  RSSI Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers. IEEE Journal of Selected topics in signal processing, 2010.
  3. S. Kim, S. Paul. E. Wan. J. McNames, Multiharmonic Frequency Tracking Method Using The Sigma-Point Kalman Smoother. EURASIP Journal on Advances in Signal Processing, vol. 2010, Article ID 467150, 13 pages, 2010. doi:10.1155/2010/467150.
  4. A. Bogdanov, E. A. Wan. State-Dependent Riccati Equation Control for Small Autonomous Helicopters. In Journal of Guidance, Control, and Dynamics, 2007 vol. 30 no. 1, pages 47-60, 2007.
  5. E. A. Wan, A. A. Bogdanov, R. Kieburtz, A. Baptista, M. Carlsson, Y. Zhang, and M. Zulauf, Model Predictive Neural Control for Aggressive Helicopter Maneuvers. In Software Enabled Control: Information Technologies for Dynamical Systems, IEEE Press, edited by Tariq Samad and Gary Balas, 2003.
  6. E. A. Wan and A. T. Nelson, Dual EKF Methods. In Kalman Filtering and Neural Networks, chapter (52 pages), Wiley Publishing, edited by Simon Haykin, 2001 
  7. E. A. Wan and R. van der Merwe, The Unscented Kalman Filter. In Kalman Filtering and Neural Networks, chapter 7. The Unscented Kalman Filter, (62 pages), Wiley Publishing, edited S. Haykin, 2001. 
  8. E. A. Wan and A. Nelson, Networks for Speech Enhancement. In Handbook of Neural Networks for Speech Processing, edited by Shigeru Katagiri, Artech House, Boston, USA. 2000. 
  9. E. A. Wan and F. Beaufays, Diagrammatic Methods for Deriving and Relating Temporal Neural Networks Algorithms, In Adaptive Processing of Sequences and Data Structures, Lecture Notes in Artificial Intelligence -Springer Verlag, editors Gori, M and C.L. Giles, 1998. 
  10. E. A. Wan and F. Beaufays. Diagrammatic Derivation of Gradient Algorithms for Neural Networks. In Neural Computations, vol. 8, no. 1, p. 182-201, 1996. 
  11. F. Beaufays and E. A. Wan. Relating Real-Time-Backpropagation and Backpropagation-Through-Time: An Application of Flow Graph Interreciprocity. In Neural Computation, vol. 6, no. 2, p. 296-306. 1994. 
  12. E. A.Wan. Discrete Time Neural Networks. In Journal of Applied Intelligence, vol 3, no. 1, p. 91-105, 1993. 
  13. E. A. Wan. Neural Network Classification: A Bayesian Interpretation. IEEE Transactions on Neural Networks, vol. 1, no. 4, p. 303-305, December 1990. 
  14. E. A. Wan. Time Series Prediction Using a Neural Network with Embedded Tapped Delay-Lines. In Predicting the Future and Understanding the Past, A. Weigend and N. Gershenfeld Editors, SFI Studies in the Science of Complexity, Proc. vol. XVII, Addison-Wesley, 1993. 
  15. E. A. Wan. Finite Impulse Response Neural Networks with Applications in Time Series Prediction. Ph.D. Dissertation, Stanford University, Nov. 1993. 

Conference proceedings

  1. A. S. Paul, E.  A. Wan and P. G. Jacobs, "Sigma-point Kalman smoothing for indoor tracking and auto-calibration using time-of-flight ranging," In proceedings of The 24th International Technical Meeting of The Institute of Navigation (ION GNSS 2011), Portland, OR, September, 2011.   
  2. P. G. Jacobs, A. S. Paul and E. A. Wan, "EmbedRF Position Tracking and Mobility Assessment System: A low-power and low-cost system for indoor pedestrian tracking and mobility assessment," In proceedings of The 24th International Technical Meeting of The Institute of Navigation (ION GNSS 2011), Portland, OR, September, 2011.   
  3. E. A. Wan and A. S. Paul, "A tag-free solution to unobtrusive indoor tracking using wall-mounted ultrasonic transducers," In proceedings of 2010 IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN), Zurich, Switzerland, September, 2010.   
  4. P.G. Jacobs, Wan, E.A., Kagen, D., & Konrad-Martin, D. Methodology for Improving Medial Olivocochlear (MOC) Reflex Measurements, American Auditory Society Annual Conference, March 2009.
  5. P. Jacobs, E. Wan, D. Konrad-Martin. On Correlating Otoacoustic Emissions with Blood Glucose. 30th Annual International IEEE EMBS Conference, Aug 2008.
  6. S. Paul and E. A. Wan. Wi-Fi Based Indoor Localization and Tracking Using Sigma-Point Kalman Filtering Methods. 2008 IEEE / Institute of Navigation – Position Location and Navigation Symposium, May 2008.
  7. S. Paul and E. A. Wan, A new formulation for nonlinear forwardbackward smoothing. International Conference on Acoustic Speech and Signal Processing (ICASSP), 2008.
  8. S. Kim, A. S. Paul, E. A. Wan, and J. McNames, Multiharmonic Tracking Using Sigma-Point Kalman Filter. 30th Annual International IEEE EMBS Conference, Aug 2008.
  9. E. A. Wan. Review of Unscented/Signal-Point Filters.  10th ONR/GTRI Workshop on Tracking and Sensor Fusion. Invited Talk. May 2007.
  10. P. Jacobs, D. Erdogmus, E. Wan, M. Leek, S. Fausti S. Development of an Audio-Visual Dual Sensory Assist Device Using Mutual Information Optimization. International Hearing Aid Research Conference, Lake Tahoe, CA, August 2006. 
  11. P. Jacobs, E. Wan, D. Konrad-Martin, D. Kagen, S. Fausti SA. Correlating Forward-Masked SFOAE with Blood Glucose in Diabetic Subjects. American Auditory Society Annual Conference, Scottsdale, AZ, March 2007. 
  12. H. Bai, E. Wan, X. Song, A. Myronenko, A. Bogdanov. Vision-only Navigation and Control of Unmanned Aerial Vehicles Using the Sigma-Point Kalman Filter. In Institute of Navigation National Technical Meeting, January 2007. 
  13. S. Paul, E. A. Wan, A. Nelson. Noise Reduction for Heart Sounds Using a Modified Minimum Mean Square Error Estimator With ECG Gating. In the IEEE 2006 International Conference of the Engineering in Medicine and Biology Society, 2006. 
  14. S. Paul and E. A. Wan. Dual Kalman Filters for Autonomous Terrain Aided Navigation in Unknown Environments, In the International Joint Conference on Neural Networks, 2005. 
  15. Bogdanov, G. Harvey, E. A. Wan. SDRE Flight Control For X-Cell And R-Max Autonomous Helicopters, In 43rd IEEE Conference on Decision and Control, 2004. 
  16. R. van der Merwe and E. A. Wan. Sigma-Point Kalman Filters for Integrated Navigation, In Institute of Navigation Annual Technical Meeting, 2004. 
  17. R. van der Merwe , E. A. Wan, S. J. Julier, A. Bogdanov, G. Harvey, J. Hunt. Sigma-Point Kalman Filters for Nonlinear Estimation and Sensor Fusion: Applications to Integrated Navigation, In AIAA Guidance, Navigation, and Controls Conference, 2004. 
  18. R. van der Merwe and E. A. Wan. Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models. In Proceedings of the Workshop on Advances in Machine Learning, Montreal, Canada, June, 2003. 
  19. R. van der Merwe and E. A. Wan. Gaussian Mixture Sigma-Point Particle Filters for Sequential Probabilistic Inference in Dynamic State-Space Models. In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hong Kong, Apr, 2003 
  20. Q. Fu, and E. A. Wan. Perceptual Wavelet Adaptive Denoising of Speech. In Eurospeech, 2003. 
  21. Bogdanov, E. A. Wan, M. Carlsson, Y. Zhang, R. Kieburtz and A. Baptista. Model predictive neural control of a high-fidelity helicopter model. In 2001 AIAA Guidance, Navigation and Control Conference., Aug 6-9, Montreal, Quebec, Canada, 2001. 
  22. Bogdanov, M. Carlsson, G. Harvey, J. Hunt, R. Kieburtz, , R. van der Merwe, E. A. Wan. State-dependent Riccati Equations control of a Small Unmanned Helicopter. In AIAA Guidance, Navigation, and Control Conference, 2003. 
  23. Bogdanov, E. A. Wan. SDRE Control with Nonlinear Feedforward Compensation for a Small Unmanned Helicopter, In 2nd AIAA Unmanned Unlimited Systems, Technologies, 2003. 
  24. R.van der Merwe and E. A. Wan. The Square-Root Unscented Kalman Filter for State and Parameter-Estimation. In International Conference on Acoustics, Speech, and Signal Processing, Salt Lake City, Utah, May, 2001. 
  25. R.van der Merwe and E. A. Wan. Efficient Derivative-Free Kalman Filters for Online Learning. In European Symposium on Artificial Neural Networks (ESANN), Bruges, Belgium, Apr, 2001. 
  26. E. A. Wan and A. Bogdanov. Model predictive neural control with applications to a 6 DoF helicopter model. In American Controls Conference, Arlington, VA, Jun, 2001. 
  27. R. van der Merwe and N. de Freitas, A. Doucet and E. A. Wan. The Unscented Particle Filter, num. CUED/F-INFENG/TR 380, Cambridge University Engineering Department, Cambridge, England, Aug, 2000. 
  28. R. van der Merwe, A. Doucet, N. de Freitas and E. A. Wan. The Unscented Particle Filter. In Advances in Neural Information Processing Systems (NIPS13), MIT Press, Eds. T. K. Leen, T. G. Dietterich and V. Tresp, Dec, 2000. 
  29. E. A. Wan and R.van der Merwe. The Unscented Kalman Filter for Nonlinear Estimations. In IEEE Symposium 2000 on Adaptive Systems for Signal Processing, Communications, and Control. Oct. 2000. 
  30. E. A. Wan and R. van der Merwe. Dual Estimation and the Unscented Transformation. In Neural Information Processing Systems, vol 12, Nov. 2000. 
  31. E. A. Wan and R. van der Merwe. Noise-regularized adaptive filtering for speech enhancement. In EUROSPEECH, 1999. 
  32. E. A. Wan and A. Nelson. Removal of Noise from Speech Using the Dual EKF Algorithm. In ICASSP, 1998. 
  33. Nelson and E. A. Wan. A Two-Observation Kalman Framework for Maximum-Likelihood Modeling of Noisy Time Series. In IJCNN, 1998. 
  34. E. A. Wan and A. Nelson. Neural Dual Extended Kalman Filtering: Applications in Speech Enhancement and Monaural Blind Signal Separation. In Neural Networks for Signal Processing VII: Proceedings of the 1997 IEEE Workshop, ed. Principe, Morgan, Giles, Wilson, 1997. 
  35. E. A. Wan. Combining Fossils and Sunspots: Committee Predictions. In International Conference on Neural Networks (ICNN), 1997. 
  36. Nelson and E. A. Wan. Neural Speech Enhancement Using Dual Extended Kalman Filtering. In International Conference on Neural Networks (ICNN), 1997. 
  37. E. A. Wan and A. Nelson. Dual Kalman Filtering Methods for Nonlinear Prediction, Estimation, and Smoothing. In Proceedings of the Neural Information Processing Systems Conference, 1996. 
  38. E. A. Wan. Adjoint LMS: An Efficient Alternative to Filtered-X LMS and Multiple Error LMS. In Proc. IEEE ICASSP, vol III, p. 1842-45, 1996. 
  39. H. Hermansky, E. A. Wan, and C. Avendano. Speech Enhancement Based on Temporal Processing. In Proc. IEEE ICASSP, Detroit, p. 405-408, 1995. 
  40. Avendano, H. Hermansky, and E. A. Wan. Beyond Nyquist: Towards the Recovery of Broad Band Speech from Narrow-Band Speech. In EUROSPEECH, Madrid, Spain, p. 165-168, 1995. 
  41. H. Hermansky, C. Avendano and E. A. Wan. Noise Reduction and Recovery of Missing Frequencies in Speech. In Proc. of the 15th Annual Speech Research Symposium, p. 124-129, Baltimore, MD, p.124-129, 1995. 
  42. H. Hermansky, E. A. Wan, and C. Avendano. Noise Suppression in cellular communications. In Proceedings of 2nd IEEE Workshop on Interactive Voice Technology for Telecommunications Applications, Kyoto, Japan, p. 85-88, 1994. 
  43. E. A. Wan and F. Beaufays. Network Reciprocity: A Simple Approach to Derive Gradient Algorithms for Arbitrary Neural Network Structures. In Proceedings of World Congress on Neural Networks, San Diego, CA, p.III/382-9 vol. 3, 1994.
  44. F. Beaufays and E. A. Wan. An Efficient First-Order Stochastic Algorithm for Lattice Filters, F. In Proceedings of International Conference on Artificial Neural Networks. Sorrento, Italy, vol. 2, p. 1021-4, 1994. 
  45. E. A. Wan. Modeling Nonlinear Dynamics with Neural Networks: Examples in Time Series Prediction. In Proceedings of the Fifth Workshop on Neural Networks: Academic/Industrial/NASA/Defense, WNN93/FNN93, San Francisco, p. 327-332, November 1993. Outstanding Paper Award. 
  46. Back, E. A. Wan, S. Lawrence, and A. Tsoi. A Unifying View of Some Training Algorithms for Multilayer Perceptrons with FIR Filter Synapses. In IEEE Workshop on Neural Networks and Signal Processing, Sep. 6-8, Ermioni, Greece, p. 146-54, 1994. 
  47. F. Beaufays and E. A. Wan. A Unified Approach to Derive Gradient Algorithms for Arbitrary Neural Network Structures. In Proceedings of International Conference on Artificial Neural Networks. Sorrento, Italy, p. 545-8 vol.1, 1994. 
  48. Widrow, M. Lehr, F. Beaufays, E. A. Wan, M. Bilello. Adaptive Signal Processing. In Proceedings of the World Conference on Neural Networks ’93, Portland, Oregon, July 12-16, 1993.
  49. Widrow, M. Lehr, F. Beaufays, E. A. Wan, M. Bilello. Stanford Neural Network Research. In Proceedings of the SPIE -The International Society for Optical Engineering, Orlando, FL, vol.1966, p. 17-29, 1993. 
  50. Widrow, M. Lehr, F. Beaufays, E. A. Wan, M. Bilello. Learning Algorithms for Adaptive Signal Processing and Control. In Proceedings of the IEEE International Conference on Neural Networks, San Francisco, CA, vol. 1, p. 1-8, San Francisco, March 1993. 
  51. Wan. Autoregressive Neural Network Prediction: Learning Chaotic Time Series and Attractors. In Proceeding of the Summer Workshop on Neural Network Computing for the Electric Power Industry, Stanford, CA, August 17-19, 1992. 
  52. Beaufays and E. A. Wan. Using Flow Graph Interreciprocity to Relate Recurrent-Backpropagation and Backpropagation-Through-Time. In Proceeding of the Summer Workshop on Neural Network Computing for the Electric Power Industry, Stanford, CA, Aug 17-19, 1992. 
  53. Wan. Temporal Backpropagation: An Efficient Algorithm for Finite Impulse Response Neural Networks. In Proceedings of the 1990 Connectionist Models Summer School, Morgan Kaufmann, p. 131-140, 1990. 
  54. Wan. Temporal Backpropagation for FIR Neural Networks. In Proceedings of the International Joint Conference on Neural Networks, San Diego, CA, vol. 1, p. 575-80, June 1990.
  55. Wan, G. Kovacs, J. Rosen and B. Widrow. Development of Neural Network Interface for Direct Control of Neuroprostheses. In Proceedings of the International Joint Conference on Neural Networks, Washington, DC, vol 2, p. 3-21, January 1990. 
  56. Wan, P. Ning and B. Widrow. Neural Tree Structured Vector Quantization. In Proceedings of the International Joint Conference on Neural Networks, Washington, DC, January 1990. 
  57. D. Andes, B. Widrow, M. Lehr and E. A. Wan. MRIII: A robust algorithm for training analog neural networks. In Proceedings of the International Joint Conference on Neural Networks, Washington, DC, vol. I, p. 533-536, January 1990.