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Frequency and noise characterization for baseband signal processing on neuromorphic circuits

Authors:: Galicia, M. , Happek, L. , Balzer, M. , Leupers, R.
Book Title:: 21st IEEE Interregional NEWCAS Conference (NEWCAS)
Date:: Jun. 2023
DOI:: 10.1109/NEWCAS57931.2023.10198095
Language:: English
Abstract:: Memristor crossbar-based systems have shown enormous
potential to further enhance applications that make extensive
use of vector-matrix multiplication, such as artificial in
neural networks. Many signal processing algorithms in wireless
communications, such as forward error correction (FEC) and
discrete Fourier transform (DFT), involve such operations and
could benefit from the desirable properties of memristor crossbars,
namely, low power consumption, low latency and high area
density. We investigate the high data rate response of memristor
crossbars including line parasitic resistance and capacitance, for
FEC and DFT applications in baseband signal processing for
wireless communications.
Download:: BibTeX