Publications associées à Distributed Compression in Acoustic Sensor Networks Using Oversampled A/D Conversion

Localized model order reduction and domain decomposition methods for coupled heterogeneous systems

Jan Sickmann Hesthaven, Niccolo' Discacciati

We propose a model order reduction technique to accurately approximate the behavior of multi-component systems without any a-priori knowledge of the coupled model. In the offline phase, we construct independent surrogate models by solving the local problem ...

Wiley2023

Quantization for Decentralized Learning Under Subspace Constraints

Ali H. Sayed, Roula Nassif, Stefan Vlaski, Marco Carpentiero

In this article, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the minimizers across the network to lie in low-dimensional subspaces. This constrained fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Observation of non-reciprocal harmonic conversion in real sounds

Hervé Lissek, Romain Christophe Rémy Fleury, Xinxin Guo

Reciprocity guarantees that in most media, sound transmission is symmetric between two points of space when the location of the source and receiver are interchanged. This fundamental law can be broken in non-linear media, often at the cost of detrimental i ...

2023

Cascaded all-optical quantization employing step-size MMI and shape-optimized power splitter

Xiaowei Zhang, Ye Tian, Jian Wu, Jijun He

As a key unit of future high-throughput communications, optical analog to digital converter (OADC) with all-optical quantizer element that simultaneously possesses high resolution, large bandwidth and compact size is highly promising. A pending issue of co ...

ELSEVIER SCI LTD2023

Unsupervised Voice Activity Detection by Modeling Source and System Information using Zero Frequency Filtering

Mathew Magimai Doss, Eklavya Sarkar

Voice activity detection (VAD) is an important pre-processing step for speech technology applications. The task consists of deriving segment boundaries of audio signals which contain voicing information. In recent years, it has been shown that voice source ...

ISCA2022

Spike-Based Sensing and Communication for Highly Energy-Efficient Sensor Edge Nodes

Mihai Adrian Ionescu, Teodor Rosca

Highly energy-efficient wireless sensor nodes are a prerequisite for a sustainable operation of the Internet of things. Therefore, classical approaches for system design based on digital signal processing are not a viable solution, but system design has to ...

IEEE2022

Energy-Efficient Design Techniques for High-Speed Wireline Serial Links

Firat Çelik

The exponential growth in computing power and multimedia services has caused a tremendous increase in data traffic in recent years. This increase in data traffic brings a strong demand for data bandwidth of electrical input/output (I/O) links and pushes th ...

EPFL2021

High-Speed ADC Design and Optimization for Wireline Links

Ayça Akkaya

The ever-growing global internet traffic has increased demand for higher speed data transmission. As the bandwidth requirements of wireline links increase, extensive digital equalization techniques are required to compensate for the high-frequency channel ...

EPFL2021

Deep Learning Approaches for Auditory Perception in Robotics

Weipeng He

Auditory perception is an essential part of a robotic system in Human-Robot Interaction (HRI), and creating an artificial auditory perception system that is on par with human has been a long-standing goal for researchers. In fact, this is a challenging res ...

EPFL2021

Low-Latency High-Bandwidth Circuit and System Design for Trigger Systems in High Energy Physics

Marcos Vinícius Silva Oliveira

The increasing luminosity in HEP (High Energy Physics) colliders demands trigger systems to be more selective. First, more information from the detector is routed to the trigger system. Second, larger parts of this information are processed together. These ...

EPFL2021

Resource Trade-Offs in Circuits and Systems: from Neurotechnology to Communications

Arda Uran

This thesis aims to explore and exploit trade-offs in integrated circuits and systems to overcome the fundamental bottlenecks faced by future data acquisition and communication systems. Specifically, we target the emerging implantable neurotechnology and t ...

EPFL2021

Multi-task Neural Network for Robust Multiple Speaker Embedding Extraction

Jean-Marc Odobez, Petr Motlicek, Weipeng He

This paper introduces a novel approach for extracting speaker embeddings from audio mixtures of multiple overlapping voices. This approach is based on a multi-task neural network. The network first extracts a latent feature for each direction. This feature ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

ASAP: a Dataset of Aligned Scores and Performances for Piano Transcription

Andrew Philip McLeod

In this paper we present Aligned Scores and Performances (ASAP): a new dataset of 222 digital musical scores aligned with 1068 performances (more than 92 hours) of Western classical piano music.The scores are provided as paired MusicXML files and quantized ...

2020

Multisensory haptic system and method

Olaf Blanke, Simon Gallo, Giulio Rognini

A computer-implemented method for operating a haptic device, the haptic device comprising a plurality of tactile displays configured to provide haptic stimuli to a user, the method including the steps of (a) processing an audio signal derived from an audio ...

2020

A 161-mW 56-Gb/s ADC-Based Discrete Multitone Wireline Receiver Data-Path in 14-nm FinFET

Yusuf Leblebici, Alessandro Cevrero, Andreas Peter Burg, Gain Kim, Lukas Kull, Thomas Toifl, Cosimo Aprile, Ilter Ozkaya

This article introduces a wireline receiver (RX) data-path employing discrete multi-tone (DMT) modulation for communicating over electrical links. The DMT RX incorporates a fully digital equalization data-path, with a synthesized and automatically placed a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Design Patterns for Resource-Constrained Automated Deep-Learning Methods

Prakhar Gupta

We present an extensive evaluation of a wide variety of promising design patterns for automated deep-learning (AutoDL) methods, organized according to the problem categories of the 2019 AutoDL challenges, which set the task of optimizing both model accurac ...

2020

Sparse and Parametric Modeling with Applications to Acoustics and Audio

Helena Peic Tukuljac

Recent advances in signal processing, machine learning and deep learning with sparse intrinsic structure of data have paved the path for solving inverse problems in acoustics and audio. The main task of this thesis was to bridge the gap between the powerfu ...

EPFL2020

Experimental demonstration of three-fold wavelength multicasting of a 64-QAM 120 Gbit/s data channel using a Kerr frequency comb and nonlinear wave mixing

Tobias Kippenberg, Martin Hubert Peter Pfeiffer, Fatemeh Alishahi, Arne Kordts, Maxim Karpov, Ahmad Fallahpour

We experimentally demonstrate three-fold wavelength multicasting of a 64-quadrature-amplitude-modulation (QAM), 120-Gbit/s data channel using a microresonator Kerr frequency comb and nonlinear wave mixing. The multicasting is achieved with a data signal an ...

SPIE-INT SOC OPTICAL ENGINEERING2019

Improved Delay Bound for a Service Curve Element with Known Transmission Rate

Jean-Yves Le Boudec, Eleni Stai, Ehsan Mohammadpour

Network calculus is often used to prove delay bounds in deterministic networks, using arrival and service curves. We consider a FIFO system that offers a rate-latency service curve and where packet transmission occurs at line rate without pre-emption. The ...

2019

High Speed SAR ADC Architectures in 28nm FDSOI CMOS

Mustafa Kilic

The demand on high speed Analog to Digital Converters (ADCs) has increased considerably the last years. From communications circuit to high speed oscilloscopes, Giga Samples per second (GS/s) ADCs are requested. With the scaling of the CMOS technology, des ...

EPFL2019