
Proof methods for robust lowrank matrix recovery
Lowrank matrix recovery problems arise naturally as mathematical formul...
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Deep Unfolding of Iteratively Reweighted ADMM for Wireless RF Sensing
We address the detection of material defects, which are inside a layered...
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PhotothermalSRNet: A Customized Deep Unfolding Neural Network for Photothermal Super Resolution Imaging
This paper presents deep unfolding neural networks to handle inverse pro...
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SuperResolution for DoublyDispersive Channel Estimation
In this work we consider the problem of identification and reconstructio...
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Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution Imaging
Blocksparse regularization is already wellknown in active thermal imag...
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PilotBased 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 ...
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PlugAndPlay Learned Gaussianmixture Approximate Message Passing
Deep unfolding showed to be a very successful approach for accelerating ...
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Classification of Spotwelded Joints in Laser Thermography Data using Convolutional Neural Networks
Spot welding is a crucial process step in various industries. However, c...
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Neurally Augmented ALISTA
It is wellestablished that many iterative sparse reconstruction algorit...
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Robust InstanceOptimal Recovery of Sparse Signals at Unknown Noise Levels
We consider the problem of sparse signal recovery from noisy measurement...
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Practical HighThroughput, NonAdaptive and NoiseRobust SARSCoV2 Testing
We propose a compressed sensingbased testing approach with a practical ...
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DeepInit Phase Retrieval
This paper shows how datadriven deep generative models can be utilized ...
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Sensor Artificial Intelligence and its Application to Space Systems – A White Paper
Information and communication technologies have accompanied our everyday...
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Efficient NoiseBlind ℓ_1Regression of Nonnegative Compressible Signals
In compressed sensing the goal is to recover a signal from as few as pos...
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Robust Recovery of Sparse Nonnegative Weights from Mixtures of PositiveSemidefinite Matrices
We consider a structured estimation problem where an observed matrix is ...
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Unsourced Multiuser Sparse Regression Codes achieve the Symmetric MAC Capacity
Unsourced randomaccess (URA) is a type of grantfree random access wit...
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GrantFree Massive Random Access With a Massive MIMO Receiver
We consider the problem of unsourced random access (URA), a grantfree ...
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NonBayesian Activity Detection, LargeScale 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...
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On the Restricted Isometry Property of Centered Self KhatriRao Products
In this work we establish the Restricted Isometry Property (RIP) of the ...
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Simultaneous structures in convex signal recovery  revisiting the convex combination of norms
In compressed sensing one uses known structures of otherwise unknown sig...
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Reconstruction Methods in THz Singlepixel Imaging
The aim of this paper is to discuss some advanced aspects of image recon...
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MOCZ for Blind ShortPacket Communication: Some Practical Aspects
We will investigate practical aspects for a recently introduced blind (n...
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SPARCs for Unsourced Random Access
This paper studies the optimal achievable performance of compressed sens...
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Sparse NonNegative Recovery from Biased Subgaussian Measurements using NNLS
We investigate nonnegative least squares (NNLS) for the recovery of spa...
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Massive MIMO Unsourced Random Access
We consider an extension of the massive unsourced random access original...
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Derandomizing compressed sensing with combinatorial design
Compressed sensing is the art of reconstructing structured ndimensional...
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Noncoherent ShortPacket Communication via Modulation on Conjugated Zeros
We introduce a novel blind (noncoherent) communication scheme, called mo...
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Towards Massive Connectivity Support for Scalable mMTC Communications in 5G networks
The fifth generation of cellular communication systems is foreseen to en...
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The SzegöAsymptotics for DoublyDispersive Gaussian Channels
We consider the timecontinuous doublydispersive channel with additive...
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Improved Scaling Law for Activity Detection in Massive MIMO Systems
In this paper, we study the problem of activity detection (AD) in a mass...
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Peter Jung
verfied profile
I am working in signal processing, information and communication
theory, data science and machine learning.