Search results for "Estimation theory"

Modeling, analysis, and simulation of MIMO mobile-to-mobile fading channels

2008

This paper' deals with the modeling, analysis, and simulation of multiple-input multiple-output (MIMO) narrowband fading channels for mobile-to-mobile communications. A stochastic MIMO mobile-to-mobile reference channel model is derived from the geometrical two-ring scattering model under the assumption that both the transmitter and the receiver are surrounded by an infinite number of local scatterers. Using a wave propagation model, the complex channel gains are derived and their statistical properties are studied. General analytical solutions are provided for the three-dimensional (3-D) space-time cross-correlation function (CCF). We show that this function can be expressed as the product…

Application of model quality evaluation to systems biology

2008

Application of model quality evaluation to the quasispecies models is presented. These models are useful for the analysis of the DNA and RNA evolution and for the description of the population dynamics of viruses and bacteria. An estimate of the parameters together with their interval of variability is computed and the quality evaluation is tested on the basis of the model prediction error capability.

Online Estimation of Discrete Densities

2013

We address the problem of estimating a discrete joint density online, that is, the algorithm is only provided the current example and its current estimate. The proposed online estimator of discrete densities, EDDO (Estimation of Discrete Densities Online), uses classifier chains to model dependencies among features. Each classifier in the chain estimates the probability of one particular feature. Because a single chain may not provide a reliable estimate, we also consider ensembles of classifier chains and ensembles of weighted classifier chains. For all density estimators, we provide consistency proofs and propose algorithms to perform certain inference tasks. The empirical evaluation of t…

Finding essential features for tracking starfish in a video sequence

2004

The paper introduces a software system for detecting and tracking starfish in an underwater video sequence. The target of such a system is to help biologists in giving an estimate of the number of starfish present in a particular area of the sea-bottom. The nature of the input images is characterised by a low signal/noise ratio and by the presence of noisy background represented by pebbles; this makes the detection a non-trivial task. The procedure we use is a chain of several steps that starts from the extraction of the area of interest and ends with a classifier and a tracker providing the necessary information for counting the starfish present in the scene. © 2003 IEEE.

Partial Discharges analysis and parameters identification by continuous Ant Colony Optimization

2008

The technique of ant colony optimization has been employed in this paper to efficiently deal with the problem of parameters identification in partial discharge, PD, analysis. The latter is a continuous optimization problem. From the technical point of view the identification of these parameters allows the modeling of the phenomenon of Partial Discharges in dielectrics. In this way it is possible the early diagnosis of defects in Medium Voltage cable lines and components and thus it is possible to prevent possible outages and service interruptions. Analytically, the problem consists of finding the Weibull parameters of the Pulse Amplitude Distribution (PAD) distributions allowing the identif…

Morphostatistical characterization of the spatial galaxy distribution through Gibbs point processes

2021

This paper proposes a morpho-statistical characterisation of the galaxy distribution through spatial statistical modelling based on inhomogeneous Gibbs point processes. The galaxy distribution is supposed to exhibit two components. The first one is related to the major geometrical features exhibited by the observed galaxy field, here, its corresponding filamentary pattern. The second one is related to the interactions exhibited by the galaxies. Gibbs point processes are statistical models able to integrate these two aspects in a probability density, controlled by some parameters. Several such models are fitted to real observational data via the ABC Shadow algorithm. This algorithm provides …

Development of an earth observation processing chain for crop bio-physical parameters at local scale

2015

This paper proposes a full Earth observation processing chaing for biophysical parameter estimation at local scales. In particular, we focus on the Leaf Area Index (LAI) as an essential climate variable required for the monitoring and modeling of land surfaces at local scale. The main goal of this study is tied to the use of optical satellite images to retrieve Earth Observation (EO) biophysical parameters able to describe the spatio-temporal changes in agro-ecosystems at local scale. The objective of this work is two-fold: (i) to set up and update the EO products processing chain at high resolution (local) scale; and (ii) derive multitemporal LAI maps at 30 m resolution to be fed into a cr…

Statistical biophysical parameter retrieval and emulation with Gaussian processes

2019

Abstract Earth observation from satellites poses challenging problems where machine learning is being widely adopted as a key player. Perhaps the most challenging scenario that we are facing nowadays is to provide accurate estimates of particular variables of interest characterizing the Earth's surface. This chapter introduces some recent advances in statistical bio-geophysical parameter retrieval from satellite data. In particular, we will focus on Gaussian process regression (GPR) that has excelled in parameter estimation as well as in modeling complex radiative transfer processes. GPR is based on solid Bayesian statistics and generally yields efficient and accurate parameter estimates, a…

Analysing Buyers' Burstiness in E-Business: Parameter Estimation and Practical Applications

2017

Identification of a static tool force model for robotic face milling

2014

In this paper two different process models which can predict the mean value components of the tool forces when milling aluminium, bronze and steel with an industrial robot have been estimated. The parameters in the process models were depth and width of cut, while feedrate and cutting speed were found from the tool manufacturer's datasheets. The models were estimated from a large set of machining experiments. Different measurement sets were used for parameter estimation and for model verification. The estimated models were found to be accurate. For the experiments in aluminium and the model using only the depth of cut as parameter, the average error was about 18N. For the model using both d…