Our projects propose to develop a brain-inspired pattern recognition algorithm for multiple tasks including robotic trajectory tracking and data classification. At the current phase, the project aims to investigate the temporal and spatial dynamics in the cerebellar network models capable of predicting cerebellar input-output transformations by analyzing the mathematical and computational properties of the neural circuits.
The proposal is to exploit biophysical neural network models to the problem of pattern recognition and navigation in mobile robots to achieve practical algorithms for specific applications like surgery or disaster mitigation. Unlike many projects, this project will rely on biological basis for design and function of a pattern classifier that can be used in motor articulation.
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