GSRC Student Profile:
Ping-Chen Huang
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University of California, Berkeley
Advisor: Jan Rabaey
GSRC theme: alternatives
Expected graduation: Jun, 2013 |
Research Overview: Bio-Inspired Sensory Signal Processing
Signal processing tasks such as classification or recognition may benefit from implementation strategies inspired by biological sensory pathways. In this project, we explore the biological system from both the top-down and bottom-up perspectives. From the top down, we explore the functional models in computational neuroscience and seek for low-power, resilient architectures that allow the use of low-power and low-precision computational units. From the bottom up, we investigate the strategies that the sensory systems have used to seamlessly interact with the analog inputs and perform asynchronous computation. An odor recognition architecture is proposed inspired by the olfactory sensory pathway. This design seamlessly interacts with the analog sensor responses and performs distributed computation with an overcomplete number of low-power, low-precision analog components, leading to energy efficiency and resiliency.
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