Abstract
In this paper we present an autonomous and adaptive digital neural signal processor to enable real-time processing of neural signals for brain machine interfaces (BMIs). The algorithms and architectures provide autonomous operation with low computational and hardware complexity. This enables localized processing of neural signals to minimize wireless bandwidth and overall power dissipation.
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