Massively Parallel Neural Signal Processing on a Many-Core Platform

Abstract

Although the ensemble empirical mode decomposition (EEMD) method and Hilbert-Huang transform (HHT) offer an unrivaled opportunity to understand neural signals, the EEMD algorithm's complexity and neural signals' massive size have hampered EEMD application. However, a new approach using a many-core platform has proven both efficient and effective for massively parallel neural signal processing.