b'Peter Jung'

research

∙ 07/04/2023

Integrated Sensing and Communication with MOCZ Waveform

In this work, we propose a waveform based on Modulation on Conjugate-rec...

0 Saeid K. Dehkordi, et al. ∙

research

∙ 04/07/2023

A physics-informed neural network framework for modeling obstacle-related equations

Deep learning has been highly successful in some applications. Neverthel...

0 Hamid El Bahja, et al. ∙

research

∙ 02/09/2023

On Discovering Interesting Combinatorial Integer Sequences

We study the problem of generating interesting integer sequences with a ...

0 Martin Svatos, et al. ∙

research

∙ 10/11/2022

Estimation of Doubly-Dispersive Channels in Linearly Precoded Multicarrier Systems Using Smoothness Regularization

In this paper, we propose a novel channel estimation scheme for pulse-sh...

0 Andreas Pfadler, et al. ∙

research

∙ 09/28/2022

Algorithm Unfolding for Block-sparse and MMV Problems with Reduced Training Overhead

In this paper we consider algorithm unfolding for the Multiple Measureme...

0 Jan Christian Hauffen, et al. ∙

research

∙ 02/07/2022

Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Countless signal processing applications include the reconstruction of s...

11 Jonathan Sauder, et al. ∙

research

∙ 09/21/2021

Pilot-Based Unsourced Random Access with a Massive MIMO Receiver: Interference Cancellation and Power Control

In this work we treat the unsourced random access problem on a Rayleigh ...

0 Alexander Fengler, et al. ∙

research

∙ 09/02/2021

Solving Inverse Problems with Conditional-GAN Prior via Fast Network-Projected Gradient Descent

The projected gradient descent (PGD) method has shown to be effective in...

24 Muhammad Fadli Damara, et al. ∙

research

∙ 07/07/2021

A Survey of Uncertainty in Deep Neural Networks

Due to their increasing spread, confidence in neural network predictions...

29 Jakob Gawlikowski, et al. ∙

research

∙ 06/08/2021

Proof methods for robust low-rank matrix recovery

Low-rank matrix recovery problems arise naturally as mathematical formul...

0 Tim Fuchs, et al. ∙

research

∙ 06/07/2021

Deep Unfolding of Iteratively Reweighted ADMM for Wireless RF Sensing

We address the detection of material defects, which are inside a layered...

0 Udaya S. K. P. Miriya Thanthrige, et al. ∙

research

∙ 04/21/2021

Photothermal-SR-Net: A Customized Deep Unfolding Neural Network for Photothermal Super Resolution Imaging

This paper presents deep unfolding neural networks to handle inverse pro...

0 Samim Ahmadi, et al. ∙

research

∙ 01/27/2021

Super-Resolution for Doubly-Dispersive Channel Estimation

In this work we consider the problem of identification and reconstructio...

0 Robert Beinert, et al. ∙

research

∙ 12/07/2020

Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution Imaging

Block-sparse regularization is already well-known in active thermal imag...

0 Samim Ahmadi, et al. ∙

research

∙ 12/06/2020

Pilot-Based Unsourced Random Access with a Massive MIMO Receiver, MRC and Polar Codes

In this work we treat the unsourced random access problem on a Rayleigh ...

0 Alexander Fengler, et al. ∙

research

∙ 11/18/2020

Plug-And-Play Learned Gaussian-mixture Approximate Message Passing

Deep unfolding showed to be a very successful approach for accelerating ...

0 Osman Musa, et al. ∙

research

∙ 10/24/2020

Classification of Spot-welded Joints in Laser Thermography Data using Convolutional Neural Networks

Spot welding is a crucial process step in various industries. However, c...

5 Linh Kästner, et al. ∙

research

∙ 10/05/2020

Neurally Augmented ALISTA

It is well-established that many iterative sparse reconstruction algorit...

0 Freya Behrens, et al. ∙

research

∙ 08/19/2020

Robust Instance-Optimal Recovery of Sparse Signals at Unknown Noise Levels

We consider the problem of sparse signal recovery from noisy measurement...

0 Hendrik Bernd Petersen, et al. ∙

research

∙ 07/17/2020

Practical High-Throughput, Non-Adaptive and Noise-Robust SARS-CoV-2 Testing

We propose a compressed sensing-based testing approach with a practical ...

0 Hendrik Bernd Petersen, et al. ∙

research

∙ 07/16/2020

DeepInit Phase Retrieval

This paper shows how data-driven deep generative models can be utilized ...

0 Martin Reiche, et al. ∙

research

∙ 06/09/2020

Sensor Artificial Intelligence and its Application to Space Systems – A White Paper

Information and communication technologies have accompanied our everyday...

0 Anko Börner, et al. ∙

research

∙ 03/29/2020

Efficient Noise-Blind ℓ_1-Regression of Nonnegative Compressible Signals

In compressed sensing the goal is to recover a signal from as few as pos...

0 Hendrik Bernd Petersen, et al. ∙

research

∙ 03/26/2020

Robust Recovery of Sparse Nonnegative Weights from Mixtures of Positive-Semidefinite Matrices

We consider a structured estimation problem where an observed matrix is ...

0 Fabian Jaensch, et al. ∙

research

∙ 01/13/2020

Unsourced Multiuser Sparse Regression Codes achieve the Symmetric MAC Capacity

Unsourced random-access (U-RA) is a type of grant-free random access wit...

0 Alexander Fengler, et al. ∙

research

∙ 11/30/2019

Grant-Free Massive Random Access With a Massive MIMO Receiver

We consider the problem of unsourced random access (U-RA), a grant-free ...

0 Alexander Fengler, et al. ∙

research

∙ 10/24/2019

Non-Bayesian Activity Detection, Large-Scale Fading Coefficient Estimation, and Unsourced Random Access with a Massive MIMO Receiver

In this paper, we study the problem of user activity detection and large...

0 Alexander Fengler, et al. ∙

research

∙ 05/22/2019

On the Restricted Isometry Property of Centered Self Khatri-Rao Products

In this work we establish the Restricted Isometry Property (RIP) of the ...

0 Alexander Fengler, et al. ∙

research

∙ 04/16/2019

Simultaneous structures in convex signal recovery - revisiting the convex combination of norms

In compressed sensing one uses known structures of otherwise unknown sig...

0 Martin Kliesch, et al. ∙

research

∙ 03/21/2019

Reconstruction Methods in THz Single-pixel Imaging

The aim of this paper is to discuss some advanced aspects of image recon...

0 Martin Burger, et al. ∙

research

∙ 02/08/2019

MOCZ for Blind Short-Packet Communication: Some Practical Aspects

We will investigate practical aspects for a recently introduced blind (n...

0 Philipp Walk, et al. ∙

research

∙ 01/18/2019

SPARCs for Unsourced Random Access

This paper studies the optimal achievable performance of compressed sens...

0 Alexander Fengler, et al. ∙

research

∙ 01/17/2019

Sparse Non-Negative Recovery from Biased Subgaussian Measurements using NNLS

We investigate non-negative least squares (NNLS) for the recovery of spa...

0 Yonatan Shadmi, et al. ∙

research

∙ 01/03/2019

Massive MIMO Unsourced Random Access

We consider an extension of the massive unsourced random access original...

0 Alexander Fengler, et al. ∙

research

∙ 12/19/2018

Derandomizing compressed sensing with combinatorial design

Compressed sensing is the art of reconstructing structured n-dimensional...

0 Peter Jung, et al. ∙

research

∙ 05/21/2018

Noncoherent Short-Packet Communication via Modulation on Conjugated Zeros

We introduce a novel blind (noncoherent) communication scheme, called mo...

0 Philipp Walk, et al. ∙

research

∙ 04/05/2018

Towards Massive Connectivity Support for Scalable mMTC Communications in 5G networks

The fifth generation of cellular communication systems is foreseen to en...

0 Carsten Bockelmann, et al. ∙

research

∙ 03/09/2018

The Szegö-Asymptotics for Doubly-Dispersive Gaussian Channels

We consider the time-continuous doubly--dispersive channel with additive...

0 Peter Jung, et al. ∙

research

∙ 03/06/2018

Improved Scaling Law for Activity Detection in Massive MIMO Systems

In this paper, we study the problem of activity detection (AD) in a mass...

0 Saeid Haghighatshoar, et al. ∙

Peter Jung

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