Kan Li

Patents

Kan Li and Jose C. Principe, “Pulse-Based Unit that Improves Digital Speech Processing,” UF Technology #15736, U.S. patent pending, May, 2015.

R. E. Mueller, A. Shivji, and Kan Li “Remote Crane Bar Code System,” U.S. Patent No.: 8146814 B2, Apr. 2012.

R. E. Mueller, A. Shivji, and Kan Li, “Remote Crane Bar Code System,” U.S. Patent No.: 7721967 B2, May 2010.

Kan Li, T. MacDougall, and D. Sloan, “System and Method for Tube Scarf Detection,” U.S. Patent Appl. No.: 20080144918, published June 2008.

Kan Li, T. MacDougall, and D. Sloan, “System and Method for Tube Scarf Detection,” World Intellectual Property Organization, Pub. No.: WO/2008/034248, published Mar. 2008.

Journal Papers

Kan Li and J. C. Principe, “The kernel adaptive autoregressive-moving-average algorithm,” IEEE Trans. Neural Networks and Learning Systems, vol. 27, no. 2, pp. 334-346, Feb. 2016.

S. Dura-Bernal, Kan Li et al., “Restoring behavior via inverse neurocontroller in a lesioned cortical spiking model driving a virtual arm,” Frontiers in Neuroprosthetics Special Issue, Feb. 2016.

] X. You, W. Guo, S. Yu, Kan Li et al., “Kernel learning for dynamic texture synthesis,” IEEE Trans. Image Process., vol. 25, no. 10, pp. 4782-4795, Aug. 2016.

L. Lu, H. Zhao, Kan Li et al., “A novel normalized sign algorithm for system identification under impulsive noise interference,” Circuits, Systems, and Signal Processing, pp. 1-22, Nov. 2015.

Conference Proceedings and Abstracts

Kan Li and J. C. Principe, “Flight Dynamics Modeling and Recognition using Finite State Machine for Automatic Insect Recognition,” IEEE International Joint Conference on Neural Networks (IJCNN), Anchorage, Alaska, May 2017. Oral Presentation

Kan Li and J. C. Principe, “Automatic insect recognition using optical flight dynamics modeled by kernel adaptive arma network,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, March 2017.

Kan Li et al., “Repairing lesions via kernel adaptive inverse control in a biomimetic model of sensorimotor cortex,” IEEE EMBS Conference on Neural Engineering, Montpellier, France, April 2015.

S. Dura-Bernal, Kan Li et al., “Repairing lesions via microstimulation in a spiking network model driving a virtual arm,” Society for Neuroscience, Washington, D.C., Nov. 2014.

S. Dura-Bernal, Kan Li et al., “Modulation of virtual arm trajectories via microstimulation in a spiking model of sensorimotor cortex,” Computational Neuroscience, Quebec City, Canada, July 2014.

Kan Li, B. Chen, J. Principe, “Kernel adaptive filtering with confidence intervals,” International Joint Conference on Neural Networks (IJCNN), Dallas, TX, Aug. 2013.

Kan Li, A. Kavcic, R. Venkataramani, and M. F. Erden, “Channels with both random errors and burst erasures: capacities, LDPC code thresholds, and code performances,” IEEE International Symposium on Information Theory, Austin, TX, June 2010. Oral Presentation

Kan Li, A. Kavcic, and M. F. Erden, “Construction of burst-erasure efficient LDPC codes for use with belief propagation decoding,” IEEE International Conference on Communications (ICC), Cape Town, South Africa, May 2010. Oral Presentation

F. Lim, Kan Li, A. Kavcic, and M. Fossorier, “Iterative ordered statistics decoding over ISI channels,” Information Storage Industry Consortium-Extremely High Density Recoding, University of Houston, TX, Mar. 2008.

Invited Lecture

Kan Li, “Towards Ultra Low-Power Pulse Based Signal Processing,” Qualcomm Research Center Lecture, San Diego, CA, 27 May 2016. Available: https://www.qualcomm.com/invention/research/university-relations/lectures