4 papers · 1 filter
Spiking Neural Networks for Communication Systems: Encoding Schemes, Learning Algorithms, and Equalization~Techniques
Eike-Manuel Edelmann
Machine learning with artificial neural networks (ANNs), provides solutions for the growing complexity of modern communication systems. This complexity, however, increases power co…
Spiking Neural Belief Propagation Decoder for LDPC Codes with Small Variable Node Degrees
Alexander von Bank, Eike-Manuel Edelmann, Jonathan Mandelbaum +1
Spiking neural networks (SNNs) promise energy-efficient data processing by imitating the event-based behavior of biological neurons. In previous work, we introduced the enlarge-lik…
Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications
Laurent Schmalen, Vincent Lauinger, Jonas Ney +5
In this paper, we highlight recent advances in the use of machine learning for implementing equalizers for optical communications. We highlight both algorithmic advances as well as…
Spiking Neural Belief Propagation Decoder for Short Block Length LDPC Codes
Alexander von Bank, Eike-Manuel Edelmann, Sisi Miao +2
Spiking neural networks (SNNs) are neural networks that enable energy-efficient signal processing due to their event-based nature. This paper proposes a novel decoding algorithm fo…