ACCEPTED MANUSCRIPT SELF-ORGANIZING MAPS WITH DYNAMIC LEARNING FOR SIGNAL RECONSTRUCTION (2008)
Jeongho Cho, Sung-phil Kim, Justin C. Sanchez, Jose C. Principe, Jeongho Cho, ...
Self-organizing maps with dynamic learning for signal reconstruction. Neural Networks
Gregory Shakhnarovich, Sung-phil Kim, Michael J. Black
physically-based models for decoding
Physically-based model for decoding motor-cortical activity (2008)
Gregory Shakhnarovich, Sung-phil Kim, Michael J. Black
A standard paradigm in decoding motor-cortical population activity, in particular in the context of neuromotor prostheses (NMP), is to infer from the recorded neural signal the kinematics of the...
Gregory Shakhnarovich, Sung-phil Kim, Michael J. Black
physically-based models for decoding
Gregory Shakhnarovich, Sung-phil Kim, Michael J. Black
physically-based models for decoding
Statistical Analysis of the Non-stationarity of Neural Population Codes ∗ (2008)
Sung-phil Kim, Frank Wood, Matthew Fellows, John P. Donoghue, Michael J. Black
Abstract — Neural prosthetic technology has moved from the laboratory to clinical settings with human trials. The motor cortical control of devices in such settings raises important questions about...
Sung-phil Kim, John D. Simeral, Leigh R. Hochberg, John P. Donoghue, Gerhard M. Friehs, Michael J. Black
neural prosthetic control of a computer cursor has been recently demonstrated by Hochberg et al. [1] using the BrainGate system (Cyberkinetics Neurotechnology Systems, Inc.). While these results...
Jeongho Cho, Sung-phil Kim, Justin C. Sanchez, José C. Príncipe
Wireless Brain Machine Interface (BMI) communication protocols are faced with the challenge of transmitting the activity of hundreds of neurons which requires large bandwidth. Previously a data...
Design and analysis of optimal decoding models for brain-machine interfaces (2005)
Thesis (Ph.D.)--University of Florida, 2005.
Sung-Phil Kim, Yadunandana N. Rao, Deniz Erdogmus, Justin C. Sanchez, Jose C. Principe
We propose the use of nonnegative matrix factorization (NMF) as a model-independent methodology to analyze neural activity. We demonstrate that, using this technique, it is possible to identify local...
Sung-Phil Kim, Yadunandana N. Rao, Deniz Erdogmus, Justin C. Sanchez, Jose C. Principe
We propose the use of nonnegative matrix factorization (NMF) as a model-independent methodology to analyze neural activity. We demonstrate that, using this technique, it is possible to identify local...