Publications related to Detection theory

The association of basic and challenging motor capacity with mobility performance and falls in young seniors

Background: Understanding the association between motor capacity (MC) (what people can do in a standardized environment), mobility performance (MP) (what people actually do in real-life) and falls is important for early detection of and counteracting on fu ...

ELSEVIER IRELAND LTD2020

Classification of tokamak plasma confinement states with convolutional recurrent neural networks

Alessandro Pau, Federico Alberto Alfredo Felici

During a tokamak discharge, the plasma can vary between different confinement regimes: low (L), high (H) and, in some cases, a temporary (intermediate state), called dithering (D). In addition, while the plasma is in H mode, edge localized modes (ELMs) can ...

2020

Distributed Fault Detection for Interconnected Large-Scale Systems: A Scalable Plug & Play Approach

Giancarlo Ferrari Trecate, Marcello Farina

In this paper, we propose a novel distributed fault detection method to monitor the state of a-possibly large scale-linear system, partitioned into interconnected subsystems. The approach hinges on the definition of a partition-based distributed Luenberger ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

A Bit Too Much? High Speed Imaging from Sparse Photon Counts

Edoardo Charbon, Claudio Bruschini, Samuel Burri

Recent advances in photographic sensing technologies have made it possible to achieve light detection in terms of a single photon. Photon counting sensors are being increasingly used in many diverse applications. We address the problem of jointly recoverin ...

IEEE2019

A Learning-Based Framework for Quantized Compressed Sensing

Volkan Cevher, Rabeeh Karimi Mahabadi, Junhong Lin

Sparse recovery from undersampled random quan- tization measurements is a recent active research topic. Previous work asserts that stable recovery can be guaranteed via the basis pursuit dequantizer (BPDQ) if the measurements number is large enough, consid ...

2019

A Sub-mu W/Channel, 16-Channel Seizure Detection and Signal Acquisition SoC Based on Multichannel Compressive Sensing

Alexandre Schmid, Reza Ranjandish

An accurate 16-channel seizure detection system-on-chip is presented, which is based on extracting features from the compressed recorded data using multichannel compressive sensing (MCS). MCS is used to reduce the transmission data rate of sparse biologica ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Gray-matter-specific MR imaging improves the detection of epileptogenic zones in focal cortical dysplasia: A new sequence called fluid and white matter suppression (FLAWS)

Xin Chen, Tobias Kober, Thomas Yu, Nan Chen

Objectives: To evaluate the diagnostic value and characteristic features of FCD epileptogenic zones using a novel sequence called fluid and white matter suppression (FLAWS). Materials and methods: Thirty-nine patients with pathologically confirmed FCD and ...

ELSEVIER SCI LTD2018

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Jean-Philippe Thiran, Martin Vetterli, Dimitris Perdios, Eric Bezzam, Adrien Georges Jean Besson, Hanjie Pan

In this paper we show that it is sufficient to recover the locations of K strong reflectors within an insonified medium from three receive elements and 2K+1 samples per element. The proposed approach leverages advances in sampling signals with a finite rat ...

IEEE2018

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Jean-Philippe Thiran, Martin Vetterli, Dimitris Perdios, Eric Bezzam, Adrien Besson, Hanjie Pan

IEEE2018

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Detection theory

The association of basic and challenging motor capacity with mobility performance and falls in young seniors

Classification of tokamak plasma confinement states with convolutional recurrent neural networks

Distributed Fault Detection for Interconnected Large-Scale Systems: A Scalable Plug & Play Approach

A Bit Too Much? High Speed Imaging from Sparse Photon Counts

A Learning-Based Framework for Quantized Compressed Sensing

A Sub-mu W/Channel, 16-Channel Seizure Detection and Signal Acquisition SoC Based on Multichannel Compressive Sensing

Gray-matter-specific MR imaging improves the detection of epileptogenic zones in focal cortical dysplasia: A new sequence called fluid and white matter suppression (FLAWS)

A Compressed Sensing Approach for Distribution Matching

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Graph Chatbot

Chat with Graph Search

The association of basic and challenging motor capacity with mobility performance and falls in young seniors

Classification of tokamak plasma confinement states with convolutional recurrent neural networks

A Learning-Based Framework for Quantized Compressed Sensing

Distributed Fault Detection for Interconnected Large-Scale Systems: A Scalable Plug & Play Approach

Gray-matter-specific MR imaging improves the detection of epileptogenic zones in focal cortical dysplasia: A new sequence called fluid and white matter suppression (FLAWS)

A Sub-mu W/Channel, 16-Channel Seizure Detection and Signal Acquisition SoC Based on Multichannel Compressive Sensing

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

A Bit Too Much? High Speed Imaging from Sparse Photon Counts

A Compressed Sensing Approach for Distribution Matching

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation