2 citations · 2 across the 7 of their papers we have counts for
9 papers
Spiking Neural Network-based Equalization and Demapping in IM/DD Systems: A Comparison
Eike-Manuel Edelmann, Alexander von Bank, Laurent Schmalen
In recent years, artificial neural networks (ANNs) have emerged as the de facto standard for addressing challenging problems in communications engineering that are difficult to sol…
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…
Encoding Optimization for Low-Complexity Spiking Neural Network Equalizers in IM/DD Systems
Eike-Manuel Edelmann, Alexander von Bank, Laurent Schmalen
Neural encoding parameters for spiking neural networks (SNNs) are typically set heuristically. We propose a reinforcement learning-based algorithm to optimize them. Applied to an S…
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…
Short-reach Optical Communications: A Real-world Task for Neuromorphic Hardware
Elias Arnold, Eike-Manuel Edelmann, Alexander von Bank +3
Spiking neural networks (SNNs) emulated on dedicated neuromorphic accelerators promise to offer energy-efficient signal processing. However, the neuromorphic advantage over traditi…
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…
Energy-efficient Spiking Neural Network Equalization for IM/DD Systems with Optimized Neural Encoding
Alexander von Bank, Eike-Manuel Edelmann, Laurent Schmalen
We propose an energy-efficient equalizer for IM/DD systems based on spiking neural networks. We optimize a neural spike encoding that boosts the equalizer's performance while decre…
Spiking Neural Network Decision Feedback Equalization for IM/DD Systems
Alexander von Bank, Eike-Manuel Edelmann, Laurent Schmalen
A spiking neural network (SNN) equalizer with a decision feedback structure is applied to an IM/DD link with various parameters. The SNN outperforms linear and artificial neural ne…