5 papers
ECNN: A Low-complex, Adjustable CNN for Industrial Pump Monitoring Using Vibration Data
Jonas Ney, Norbert Wehn
Industrial pumps are essential components in various sectors, such as manufacturing, energy production, and water treatment, where their failures can cause significant financial an…
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…
Efficient FPGA Implementation of an Optimized SNN-based DFE for Optical Communications
Mohamed Moursi, Jonas Ney, Bilal Hammoud +1
The ever-increasing demand for higher data rates in communication systems intensifies the need for advanced non-linear equalizers capable of higher performance. Recently artificial…
Achieving High Throughput with a Trainable Neural-Network-Based Equalizer for Communications on FPGA
Jonas Ney, Norbert Wehn
The ever-increasing data rates of modern communication systems lead to severe distortions of the communication signal, imposing great challenges to state-of-the-art signal processi…
CNN-Based Equalization for Communications: Achieving Gigabit Throughput with a Flexible FPGA Hardware Architecture
Jonas Ney, Christoph Füllner, Vincent Lauinger +3
To satisfy the growing throughput demand of data-intensive applications, the performance of optical communication systems increased dramatically in recent years. With higher throug…