Search results for "filter"
showing 10 items of 1019 documents
Uniform ergodicity of the iterated conditional SMC and geometric ergodicity of particle Gibbs samplers
2018
We establish quantitative bounds for rates of convergence and asymptotic variances for iterated conditional sequential Monte Carlo (i-cSMC) Markov chains and associated particle Gibbs samplers. Our main findings are that the essential boundedness of potential functions associated with the i-cSMC algorithm provide necessary and sufficient conditions for the uniform ergodicity of the i-cSMC Markov chain, as well as quantitative bounds on its (uniformly geometric) rate of convergence. Furthermore, we show that the i-cSMC Markov chain cannot even be geometrically ergodic if this essential boundedness does not hold in many applications of interest. Our sufficiency and quantitative bounds rely on…
Energy efficient modulation of dendritic processing functions
1998
The voltage dependent ionic conductances and the passive properties of the neural membrane determine how external inputs are processed by the dendritic tree, and define the computational characteristics of neurons. However, what controls these characteristics and how they are implemented at the single neuron level, in such a way that an external input results in the coding of the appropriate output, is essentially unknown. We show here that a slow inactivation of the Na+ channel, involved in the attenuation and/or failure of APs in the dendrites, acts as an active and energy efficient filter of synaptic input, and results in an activity-dependent control of the properties of individual neur…
Steady-state and tracking analysis of a robust adaptive filter with low computational cost
2007
This paper analyses a new adaptive algorithm that is robust to impulse noise and has a low computational load [E. Soria, J.D. Martin, A.J. Serrano, J. Calpe, and J. Chambers, A new robust adaptive algorithm with low computacional cost, Electron. Lett. 42 (1) (2006) 60-62]. The algorithm is based on two premises: the use of the cost function often used in independent component analysis and a fuzzy modelling of the hyperbolic tangent function. The steady-state error and tracking capability of the algorithm are analysed using conservation methods [A. Sayed, Fundamentals of Adaptive Filtering, Wiley, New York, 2003], thus verifying the correspondence between theory and experimental results.
Thermoelastic Stress Analysis by Means of a Standard Thermocamera and a 2D-Fft Based Lock-In Technique
2007
The thermoelastic effect in a generic orthotropic body under adiabatic and linear elastic stress conditions induces small and reversible temperature changes that can be correlated with the stress field by means of linear relationships. Infrared techniques are mainly used to measure temperature changes on the component surface [1], while adiabatic conditions are generally achieved by applying cyclic loads above a threshold frequency. The resolution resulting from implementing a Thermoelastic Stress Analysis (TSA) technique is a combination of the infrared acquiring system resolution and of the signal post-processing procedure. State of the art infrared detectors have NETD (Noise Equivalent T…
TB-Structure: Collective Intelligence for Exploratory Keyword Search
2017
In this paper we address an exploratory search challenge by presenting a new (structure-driven) collaborative filtering technique. The aim is to increase search effectiveness by predicting implicit seeker’s intents at an early stage of the search process. This is achieved by uncovering behavioral patterns within large datasets of preserved collective search experience. We apply a specific tree-based data structure called a TB (There-and-Back) structure for compact storage of search history in the form of merged query trails – sequences of queries approaching iteratively a seeker’s goal. The organization of TB-structures allows inferring new implicit trails for the prediction of a seeker’s i…
Supercapacitor diagnosis using an Extended Kalman Filtering approach
2016
This paper deals with the model-based analysis of a Supercapacitor for diagnostic purposes. A two legs nonlinear physical model is assumed for the Supercapacitor and the corresponding second-order nonlinear state-space mathematical model is obtained. Then, an Extended Kalman Filter is tuned so that the estimated outputs reproduce the voltages at the equivalent capacitance terminals; they give information on the state of health of the supercapacitor but are not directly measurable. In particular, an optimization problem is firstly formulated, involving the experimental input-output data and those given by the Extended Kalman Filter.
Diagnostic of Supercapacitors based on State Estimation through Extended Kalman Filter
This thesis aimed to analyze the supercapacitor behavior to verify the possibility of the estimation of its internal parameters for diagnostic purposes. The target has been reached firstly by a theoretical analysis which showed that the crucial parameters for diagnostic purposes are the voltage of the non-linear capacitance, since it gives a measure of the stored charge, and the parasitic resistance which limits the maximum allowable current and influences losses. Secondly it has been verified when a supercapacitor parameters are observable and finally an extended Kalman filter to obtain such parameters has been set up. The Thesis demonstrated that a supercapacitor can be modelled by a 2-br…
A Decisional Multi-Agent Framework for Automatic Supply Chain Arrangement
2013
In this work, a multi-agent system (MAS) for supply chain dynamic configuration is proposed. The brain of each agent is composed of a Bayesian Decision Network (BDN); this choice allows the agent for taking the best decisions estimating benefits and potential risks of different strategies, analyzing and managing uncertain information about the collaborating companies. Each agent collects information about customer's orders and current market prices, and analyzes previous experiences of collaborations with trading partners. The agent therefore performs a probabilistic inferential reasoning to filter information modeled in its knowledge base in order to achieve the best performance in the sup…
2014
For locating inaccurate problem of the discrete localization criterion proposed by Demigny, a new criterion expression of “good localization” is proposed. Firstly, a discrete expression of good detection and good localization criterion of two dimension edge detection operator is employed, and then an experiment to measure optimal parameters of two dimension Canny's edge detection operator is introduced after. Moreover, a detailed performance comparison and analysis of two dimension optimal filter obtained via utilizing tensor product for one dimension optimal filter are provided which can prove that least square support vector regression (LS-SVR) is a smoothness filter and give the construc…