14 citations · 21 across the 10 of their papers we have counts for
11 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…
Real-Time FPGA Demonstrator of ANN-Based Equalization for Optical Communications
Jonas Ney, Patrick Matalla, Vincent Lauinger +3
In this work, we present a high-throughput field programmable gate array (FPGA) demonstrator of an artificial neural network (ANN)-based equalizer. The equalization is performed an…
Fully-blind Neural Network Based Equalization for Severe Nonlinear Distortions in 112 Gbit/s Passive Optical Networks
Vincent Lauinger, Patrick Matalla, Jonas Ney +3
We demonstrate and evaluate a fully-blind digital signal processing (DSP) chain for 100G passive optical networks (PONs), and analyze different equalizer topologies based on neural…
A Hybrid Approach combining ANN-based and Conventional Demapping in Communication for Efficient FPGA-Implementation
Jonas Ney, Bilal Hammoud, Norbert Wehn
In communication systems, Autoencoder (AE) refers to the concept of replacing parts of the transmitter and receiver by artificial neural networks (ANNs) to train the system end-to-…
Unsupervised ANN-Based Equalizer and Its Trainable FPGA Implementation
Jonas Ney, Vincent Lauinger, Laurent Schmalen +1
In recent years, communication engineers put strong emphasis on artificial neural network (ANN)-based algorithms with the aim of increasing the flexibility and autonomy of the syst…
Blind and Channel-agnostic Equalization Using Adversarial Networks
Vincent Lauinger, Manuel Hoffmann, Jonas Ney +2
Due to the rapid development of autonomous driving, the Internet of Things and streaming services, modern communication systems have to cope with varying channel conditions and a s…
HALF: Holistic Auto Machine Learning for FPGAs
Jonas Ney, Dominik Loroch, Vladimir Rybalkin +3
Deep Neural Networks (DNNs) are capable of solving complex problems in domains related to embedded systems, such as image and natural language processing. To efficiently implement…