Search results for " Telecommunication"
showing 10 items of 996 documents
Algebraic parameter estimation of a multi-sinusoidal waveform signal from noisy data
2013
International audience; In this paper, we apply an algebraic method to estimate the amplitudes, phases and frequencies of a biased and noisy sum of complex exponential sinusoidal signals. Let us stress that the obtained estimates are integrals of the noisy measured signal: these integrals act as time-varying filters. Compared to usual approaches, our algebraic method provides a more robust estimation of these parameters within a fraction of the signal's period. We provide some computer simulations to demonstrate the efficiency of our method.
Algebraic parameter estimation of a biased sinusoidal waveform signal from noisy data
2012
International audience; The amplitude, frequency and phase of a biased and noisy sum of two complex exponential sinusoidal signals are estimated via new algebraic techniques providing a robust estimation within a fraction of the signal period. The methods that are popular today do not seem able to achieve such performances. The efficiency of our approach is illustrated by several computer simulations.
Tolerating malicious monitors in detecting misbehaving robots
2008
This paper considers a multi–agent system and focuses on the detection of motion misbehavior. Previous work by the authors proposed a solution, where agents act as local monitors of their neighbors and use locally sensed information as well as data received from other monitors. In this work, we consider possible failure of monitors that may send incorrect information to their neighbors due to spontaneous or even malicious malfunctioning. In this context, we propose a distributed software architecture that is able to tolerate such failures. Effectiveness of the proposed solution is shown through preliminary simulation results.
Opinion dynamics in social networks through mean field games
2016
Emulation, mimicry, and herding behaviors are phenomena that are observed when multiple social groups interact. To study such phenomena, we consider in this paper a large population of homogeneous social networks. Each such network is characterized by a vector state, a vector-valued controlled input, and a vector-valued exogenous disturbance. The controlled input of each network aims to align its state to the mean distribution of other networks' states in spite of the actions of the disturbance. One of the contributions of this paper is a detailed analysis of the resulting mean-field game for the cases of both polytopic and $mathcal L_2$ bounds on controls and disturbances. A second contrib…
Using Inverse Reinforcement Learning with Real Trajectories to Get More Trustworthy Pedestrian Simulations
2020
Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior is then derived using a greedy policy with respect to this value function. Nevertheless, sometimes the learned policy does not meet expectations, and the task of authoring is difficult and unsafe because the modification of one value or parameter in the learned value function has unpredictable consequences in the space of the policies it represents…
Nonlinear statistical retrieval of surface emissivity from IASI data
2017
Emissivity is one of the most important parameters to improve the determination of the troposphere properties (thermodynamic properties, aerosols and trace gases concentration) and it is essential to estimate the radiative budget. With the second generation of infrared sounders, we can estimate emissivity spectra at high spectral resolution, which gives us a global view and long-term monitoring of continental surfaces. Statistically, this is an ill-posed retrieval problem, with as many output variables as inputs. We here propose nonlinear multi-output statistical regression based on kernel methods to estimate spectral emissivity given the radiances. Kernel methods can cope with high-dimensi…
Secure and efficient verification for data aggregation in wireless sensor networks
2017
Summary The Internet of Things (IoT) concept is, and will be, one of the most interesting topics in the field of Information and Communications Technology. Covering a wide range of applications, wireless sensor networks (WSNs) can play an important role in IoT by seamless integration among thousands of sensors. The benefits of using WSN in IoT include the integrity, scalability, robustness, and easiness in deployment. In WSNs, data aggregation is a famous technique, which, on one hand, plays an essential role in energy preservation and, on the other hand, makes the network prone to different kinds of attacks. The detection of false data injection and impersonation attacks is one of the majo…
Subjective Logic-Based In-Network Data Processing for Trust Management in Collocated and Distributed Wireless Sensor Networks
2018
While analyzing an explosive amount of data collected in today’s wireless sensor networks (WSNs), the redundant information in the sensed data needs to be handled. In-network data processing is a technique which can eliminate or reduce such redundancy, leading to minimized resource consumption. On the other hand, trust management techniques establish trust relationships among nodes and detect unreliable nodes. In this paper, we propose two novel in-network data processing schemes for trust management in static WSNs. The first scheme targets at networks, where sensor nodes are closely collocated to report the same event. Considering both spatial and temporal correlations, this scheme generat…
Two novel subjective logic-based in-network data processing schemes in wireless sensor networks
2016
Wireless sensor networks (WSNs) consist of connected low-cost and small-size sensor nodes. The sensor nodes are characterized by various limitations, such as energy availability, processing power, and storage capacity. Typically, nodes collect data from an environment and transmit the raw or processed data to a sink. However, the collected data contains often redundant information. An in-network processing scheme attempts to eliminate or reduce such redundancy in sensed data. In this paper, we propose two in-network data processing schemes for WSNs, which are built based on a lightweight algebra for data processing. The schemes bring also benefits like decreased network traffic load and inc…
Recent advances of the multipactor RF breakdown in RF satellite microwave passive devices
2016
The main goal of this work is the review of the recent advances in the study of the multipactor RF breakdown phenomenon in RF satellite microwave passive devices for space telecommunication applications developed in the Val Space Consortium. In this work several topics related with the multipactor phenomenon will be discussed.