Search results for "parameter estimation"
showing 10 items of 33 documents
Orthogonal Multicarrier Transmission with Modal Channel Estimation
2009
A novel multi-carrier orthogonal transmission scheme is presented. While being simpler to implement, it has a spectral efficiency and design parameters similar to those of Orthogonal Frequency Division Multiplexing based on Offset Quadrature Amplitude Modulation (OFDM/OQAM). A parametric channel estimation technique is subsequently reported. The proposed technique is based on an algorithm obtained from classic Multiple Signal Classification (MUSIC) by relaxation of the hypothesis on the number of measurements with respect to the number of sensors. Numerical simulations show that our proposal outperforms previous works in this field.
Assistive robotic walker parameter identification for estimation of human thrust without force sensors
2017
In this paper we propose a parameter identification procedure for the wheel-motor dynamic of a robotic walker, i.e. a commercial trolley for elderly people endowed with cognitive, sensing and guidance capabilities. The objective of the wheel-motor dynamic model is to generate a suitable time reference to be used in an estimation algorithm. The ultimate goal of the estimation algorithm is to retrieve the thrust, i.e. torque and force, that the older adult user of the robotic walker applies to the platform. These quantities are of paramount importance in order to adopt intelligent and comfortable walker guidance algorithms. The novelty of this approach is the avoidance of additional costly se…
Multispectral image denoising with optimized vector non-local mean filter
2016
Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to develop techniques to attenuate the impact of noise, while maintaining the integrity of relevant information in images. We propose in this work to extend the application of the Non-Local Means filter (NLM) to the vector case and apply it for denoising multispectral images. The objective is to benefit from the additional information brought by multispectral imaging systems. The NLM filter exploits the redundancy of information in an image to remove noise. A …
A multivariate Gompertz-type distribution
2009
Multivariate extensions of the Gompertz distribution are plausible models for the study of several dependent populations with a Gompertz law of growth or multivariate survival data. In this paper we introduce a multivariate distribution with univariate marginal distributions of Gompertz-type form. The new distribution is expressed in closed form and shows symmetry in the component variables. We provide explicit expressions for the first moments which are functions of the Euler constant. Specifically we develop a trivariate Gompertz-type distribution and afterwards consider the multivariate case as an immediate extension of this. The problem of estimating the parameters of the new multivaria…
Parameter identification of linear induction motor model in extended range of operation by means of input-output data
2012
This paper proposes a technique for the off-line estimation of the electrical parameters of the equivalent circuit of linear induction machines (LIM), taking into consideration the end effects, and focuses on the application of an algorithm based on the minimization of a suitable cost function involving the differences of measured and computed by simulation inductor current components. This method exploits an entire start-up transient of the LIM to estimate all the 4 electrical parameters of the machine (Rs, L s, σ Ls, Tr). It proposes also a set of tests to be made to estimate the variation of the magnetic parameters of the LIM versus the magnetizing current as well as the magnetizing curv…
Quantifying uncertainty in high resolution biophysical variable retrieval with machine learning
2022
The estimation of biophysical variables is at the core of remote sensing science, allowing a close monitoring of crops and forests. Deriving temporally resolved and spatially explicit maps of parameters of interest has been the subject of intense research. However, deriving products from optical sensors is typically hampered by cloud contamination and the trade-off between spatial and temporal resolutions. In this work we rely on the HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm to generate long gap-free time series of Landsat surface reflectance data by fusing MODIS and Landsat reflectances. An artificial neural network is trained on PROSAIL inversion to p…
Identification of Mg(OH)2 precipitation kinetics with population balances and CFD
Modelling, Simulation and Characterization of a Supercapacitor in Automotive Applications
2022
In the energy storage field, supercapacitors (SCs) are gaining more and more attention thanks to features such as high-power density, high life cycles and lack of maintenance. In this article, an improved SC three-branches model which considers the residual charge phenomenon is presented. The procedure to estimate the model parameters and the related experimental set-up are presented. The parameter estimation procedure is repeated for several SCs of the same type. The average parameters are then obtained and used as initial guesses for a recursive least square optimization algorithm, to increase the accuracy of the model. The model of a single SC is then extended to SC banks, testing differ…
Search for the Rare Leptonic Decay B+→μ+νμ
2004
A search for the rare leptonic decay with data collected at the resonance by the BABAR experiment was carried out. The decay rate was sensitive to the product of the Cabibbo Kobayashi Maskawa matrix element (Vub and the B decay constant fb, which was propotional to the wave function for zero separation between the quarks. The data used in the analysis was collectd with BABAR detector at the PEP-II storage ring and the sample consisted of an integrity luminosity of 81.4 fb-1. The systematic uncertainty in the signal efficiency was evaluated which included the muon candidate selection and the reconstruction efficiency of the companion B.
Precise measurement of the neutrino mixing parameter θ23 from muon neutrino disappearance in an off-axis beam
2014
New data from the T2K neutrino oscillation experiment produce the most precise measurement of the neutrino mixing parameter theta_{23}. Using an off-axis neutrino beam with a peak energy of 0.6 GeV and a data set corresponding to 6.57 x 10^{20} protons on target, T2K has fit the energy-dependent nu_mu oscillation probability to determine oscillation parameters. Marginalizing over the values of other oscillation parameters yields sin^2 (theta_{23}) = 0.514 +0.055/-0.056 (0.511 +- 0.055), assuming normal (inverted) mass hierarchy. The best-fit mass-squared splitting for normal hierarchy is Delta m^2_{32} = (2.51 +- 0.10) x 10^{-3} eV^2/c^4 (inverted hierarchy: Delta m^2_{13} = (2.48 +- 0.10) …