Search results for " processing"
showing 10 items of 7549 documents
Performance analysis of user-centric SBS deployment with load balancing in heterogeneous cellular networks: A Thomas cluster process approach
2020
Abstract In conventional heterogeneous cellular networks (HCNets), the locations of user equipments (UEs) and base stations (BSs) are modeled randomly using two different homogeneous Poisson point processes (PPPs). However, this might not be a suitable assumption in case of UE distribution because UE density is not uniform everywhere in HCNets. Keeping in view the existence of nonuniform UEs, the small base stations (SBSs) are assumed to be deployed in the areas with high UE density, which results in correlation between UEs and BS locations. In this paper, we analyse the performance of HCNets with nonuniform UE deployment containing a union of clustered and uniform UE sets. The clustered UE…
Practical considerations for acoustic source localization in the IoT era: Platforms, energy efficiency, and performance
2019
The rapid development of the Internet of Things (IoT) has posed important changes in the way emerging acoustic signal processing applications are conceived. While traditional acoustic processing applications have been developed taking into account high-throughput computing platforms equipped with expensive multichannel audio interfaces, the IoT paradigm is demanding the use of more flexible and energy-efficient systems. In this context, algorithms for source localization and ranging in wireless acoustic sensor networks can be considered an enabling technology for many IoT-based environments, including security, industrial, and health-care applications. This paper is aimed at evaluating impo…
Learning Automata-based Misinformation Mitigation via Hawkes Processes
2021
AbstractMitigating misinformation on social media is an unresolved challenge, particularly because of the complexity of information dissemination. To this end, Multivariate Hawkes Processes (MHP) have become a fundamental tool because they model social network dynamics, which facilitates execution and evaluation of mitigation policies. In this paper, we propose a novel light-weight intervention-based misinformation mitigation framework using decentralized Learning Automata (LA) to control the MHP. Each automaton is associated with a single user and learns to what degree that user should be involved in the mitigation strategy by interacting with a corresponding MHP, and performing a joint ra…
An Scalable matrix computing unit architecture for FPGA and SCUMO user design interface
2019
High dimensional matrix algebra is essential in numerous signal processing and machine learning algorithms. This work describes a scalable square matrix-computing unit designed on the basis of circulant matrices. It optimizes data flow for the computation of any sequence of matrix operations removing the need for data movement for intermediate results, together with the individual matrix operations’ performance in direct or transposed form (the transpose matrix operation only requires a data addressing modification). The allowed matrix operations are: matrix-by-matrix addition, subtraction, dot product and multiplication, matrix-by-vector multiplication, and matrix by scalar multiplication.…
Remote interspecies interactions: Improving humans and animals wellbeing through mobile playful spaces
2019
[EN] Play is an essential activity for both humans and animals as it provides stimulation and favors cognitive, physical and social development. This paper proposes a novel pervasive playful environment that allows hospitalized children to participate in remote interspecies play with dogs in a dog daycare facility, while it also allows the dogs to play by themselves with the pervasive system. The aim of this playful interactive space is to help improving both children¿s and animal¿s wellbeing and their relationships by means of technologically mediated play, while creating a solid knowledge base to define the future of pervasive interactive environments for animals.
Moving Learning Machine Towards Fast Real-Time Applications: A High-Speed FPGA-based Implementation of the OS-ELM Training Algorithm
2018
Currently, there are some emerging online learning applications handling data streams in real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been successfully used in real-time condition prediction applications because of its good generalization performance at an extreme learning speed, but the number of trainings by a second (training frequency) achieved in these continuous learning applications has to be further reduced. This paper proposes a performance-optimized implementation of the OS-ELM training algorithm when it is applied to real-time applications. In this case, the natural way of feeding the training of the neural network is one-by-one, i.e., training the neur…
Classes of sum-of-cisoids processes and their statistics for the modeling and simulation of mobile fading channels
2013
Published version of an article in the journal: EURASIP Journal on Wireless Communications and Networking. Also available from the publisher at: http://dx.doi.org/10.1186/1687-1499-2013-125 Open access In this paper, we present a fundamental study on the stationarity and ergodicity of eight classes of sum-of-cisoids (SOC) processes for the modeling and simulation of frequency-nonselective mobile Rayleigh fading channels. The purpose of this study is to determine which classes of SOC models enable the design of channel simulators that accurately reproduce the channel’s statistical properties without demanding information on the time origin or the time-consuming computation of an ensemble ave…
Noise assisted image processing by ensembles of R-SETs
2017
AbstractWe study how noise can assist the processing of an image in a resistance-single electron transistor (R-SET) model. The image is an 8-bit black and white picture. Every grey level is codified linearly into a sub-threshold input potential applied for a prescribed time window to an ensemble of R-SETs that transforms it into a spiking frequency. The addition of a background white noise potential of high amplitude permits the ensemble to process the image by means of the stochastic resonance phenomenon. Aside from the positive aspects, we analyse the negative impact of using noise and how we can minimize it using redundancy and a longer measuring time. The results are compared with the c…
A group-based wireless body sensors network using energy harvesting for soccer team monitoring
2016
[EN] In team-based sports, it is difficult to monitor physical state of each athlete during the match. Wearable body sensors with wireless connections allow having low-power and low-size devices, that may use energy harvesting, but with low radio coverage area but the main issue comes from the mobility. This paper presents a wireless body sensors network for soccer team players' monitoring. Each player has a body sensor network that use energy harvesting and each player will be a node in the wireless sensor network. This proposal is based on the zone mobility of the players and their dynamism. It allows knowing the physical state of each player during the whole match. Having fast updates an…
A Comparative Evaluation of a Virtual Reality Table and a HoloLens-Based Augmented Reality System for Anatomy Training
2020
Anatomy training with real cadavers poses many practical problems for which new training and educational solutions have been developed making use of technologies based on real-time 3-D graphics. Although virtual reality (VR) and augmented reality (AR) have been previously used in the medical field, it is not easy to select the right 3-D technology or setup for each particular problem. For this reason, this article presents a comprehensive comparative study with 82 participants between two different 3-D interactive setups: an optical-based AR setup, implemented with a Microsoft HoloLens device, and a semi-immersive setup based on a VR Table. Both setups are tested using an anatomy training s…