Search results for "Networking & Telecommunications"

Presentations of constrained systems with unconstrained positions

2005

International audience; We give a polynomial-time construction of the set of sequences that satisfy a finite-memory constraint defined by a finite list of forbidden blocks, with a specified set of bit positions unconstrained. Such a construction can be used to build modulation/error-correction codes (ECC codes) like the ones defined by the Immink-Wijngaarden scheme in which certain bit positions are reserved for ECC parity. We give a lineartime construction of a finite-state presentation of a constrained system defined by a periodic list of forbidden blocks. These systems, called periodic-finite-type systems, were introduced by Moision and Siegel. Finally, we present a linear-time algorithm for con…

Improving IoT Communications Based on Smart Routing Algorithms

2018

International audience; Due to the recorded success by Internet of Things (IoT) technology, more and more domains use it as a communications and exchange network such as e-health, smart cities, vehicles, etc. IoT don’t stop integrating an important number of components and objects that are characterized by their complexity and heterogeneity. Such constraints make the existing routings protocols unsuitable for IoT communications. To accomplish all the expected tasks and satisfy the user services, it is important to guarantee a quality of communication that answers to the requirements of the various applications in terms of data and processing (availability, integrity, efficiency, etc.). The …

Frequency Stability Measurement of Cryogenic Sapphire Oscillators with a Multichannel Tracking DDS and the Two-Sample Covariance

2018

This article shows the first measurement of three 100 MHz signals exhibiting fluctuations from 2E-16 to parts in 1E-15 for integration time tau between 1 s and 1 day. Such stable signals are provided by three Cryogenic Sapphire Oscillators (CSOs) operating at about 10 GHz, also delivering the 100 MHz output via a dedicated synthesizer. The measurement is made possible by a 6-channel Tracking DDS (TDDS) and the two-sample covariance tool, used to estimate the Allan variance. The use of two TDDS channels per CSO enables high rejection of the instrument background noise. The covariance outperforms the Three-Cornered Hat (TCH) method in that the background converges to zero "out of the box," wi…

A Deep Learning Model for Automatic Sleep Scoring using Multimodality Time Series

2021

Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. Automatic sleep scoring is crucial and urgent to help address the increasing unmet need for sleep research. Therefore, this paper aims to develop an end-to-end deep learning architecture using raw polysomnographic recordings to automate sleep scoring. The proposed model adopts two-dimensional convolutional neural networks (2D-CNN) to automatically learn features from multi-modality signals, together with a "squeeze and excitation" block for recalibrating channel-wise feature responses. The learnt representations are finally fed to a softmax classifier to generate predictions for each sleep stage. The model pe…

Fast 3D Ray Tracing for Indoor Coverage Solutions

2016

Optimal wireless indoor network planning requires huge number of iterations and evaluations of indoor coverage for each antenna location until an optimal solution is reached. Consequently, accurate and scalable calculation of power strength for indoor scenarios becomes necessary. The contribution in this paper is to reduce the complexity of 3D ray tracing for deterministic indoor power prediction. In order to achieve that while preserving the accuracy, image theory with feasible reflection volume as preprocessing approach is introduced. This proposed algorithm stores the image, its feasible reflection volume and valid area of receiving points. Significant complexity reduction is achieved by…

Learning-based multiresolution transforms with application to image compression

2013

In Harten's framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact and predicted values. In this paper we use tools of statistical learning in order to design a more accurate prediction operator in this framework based on a training sample, resulting in multiresolution decompositions with enhanced sparsity. In the case of images, we incorporate edge detection techniques in the design of the prediction operator in order to avoid Gibbs phenomenon. Numerical tests are presented showing that the …

Perceptual image quality assessment using a normalized Laplacian pyramid

2016

Localization-Free Power Cartography

2018

Author's accepted manuscript (postprint). © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Spectrum cartography constructs maps of metrics such as channel gain or received signal power across a geographic area of interest using measurements of spatially distributed sensors. Applications of these maps include network planning, interference coordination, power con…

Facilitating IP deployment in a MARTE-based MDE methodology using IP-XACT: a XILINX EDK case study

2012

International audience; In this paper we present framework for the deployment of hardware IPs at high-levels of abstraction. It is based in a model- driven approach that aims at the automatic generation of Dynamic Partial Reconfiguration designs created in Xilinx Platform Studio (XPS). Contrary to previous approaches, we make use of the IP-XACT standard to facilitate the deployment of hardware IPs, their parameterization and subsequent integration. We propose an extension to the MARTE profile for IP deployment, and we introduce the necessary model transformations to obtain a high- level representation from an IP-XACT component library. These models are then used to create a platform in MART…

Design and implementation of a long-range low-power wake-up radio and customized DC-MAC protocol for LoRaWAN

2019

In this paper, we present the design and implementation of a long-rage wake-up radio (WuR) and customized duty cycled (DC) MAC protocol for wireless IoT devices. The WuRx achieves a sensivity of −70 dBm by consuming just 0.032 mA, thereby optimizing the energy consumption of battery powered long-range wireless IoT devices. Reducing the power consumption of these devices minimizes the overall costs when deployed in large scale.