Search results for "ESA"
showing 10 items of 11914 documents
Recycling Gibbs sampling
2017
Gibbs sampling is a well-known Markov chain Monte Carlo (MCMC) algorithm, extensively used in signal processing, machine learning and statistics. The key point for the successful application of the Gibbs sampler is the ability to draw samples from the full-conditional probability density functions efficiently. In the general case this is not possible, so in order to speed up the convergence of the chain, it is required to generate auxiliary samples. However, such intermediate information is finally disregarded. In this work, we show that these auxiliary samples can be recycled within the Gibbs estimators, improving their efficiency with no extra cost. Theoretical and exhaustive numerical co…
Are simple striate cells analysers of visual signals both in spatial position as well as in spatial frequency?
1984
According to a modern view, simple cells of the cat striate cortex are considered to operate as apart of Fourier analysis system thus leading to the idea that the operational mechanism of the visual cortex is concerned with the analysis of spatial frequencies. Nevertheless if simple cells are really concerned only with the analysis of spatial frequencies there should exist a strict relationship between their spatial frequency selectivity and the spatial organization of their receptive fields. This is because it is the spatial organization of the spatial frequency detector i.e. the cell's receptive field that determines the cell's spatial frequency selectivity. Since the quantitative analysi…
Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval
2013
Abstract ESA’s upcoming Sentinel-2 (S2) Multispectral Instrument (MSI) foresees to provide continuity to land monitoring services by relying on optical payload with visible, near infrared and shortwave infrared sensors with high spectral, spatial and temporal resolution. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods, which ideally should provide uncertainty intervals for the predictions. Statistical learning regression algorithms are powerful candidats for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. In this paper, we f…
Radio Frequency Spectrum Sensing by Automatic Modulation Classification in Cognitive Radio System Using Multiscale Deep CNN
2022
Automatic modulation categorization (AMC) is used in many applications such as cognitive radio, adaptive communication, electronic reconnaissance, and non-cooperative communications. Predicting the modulation class of an unknown radio signal without having any prior information of the signal parameters is challenging. This paper proposes a novel multiscale deep-learning-based approach for the automatic modulation classification using radio signals. The approach considered the fixed boundary range-based Empirical wavelet transform (FBREWT) based multiscale analysis technique to decompose the radio signal into sub-band signals or modes. The sub-band signals computed from the radio signal comb…
SINR analysis of OFDM systems using a geometry-based underwater acoustic channel model
2015
The Doppler effect is caused by the relative movement between the transmitter (Tx) and the receiver (Rx) and/or the surface motion (waves) in underwater acoustic (UWA) communication systems. The inter-channel interference (ICI) caused by the Doppler effect degrades the performance of orthogonal frequency-division multiplexing (OFDM) systems over UWA channels. This paper is devoted to the ICI plus noise analysis of UWA-OFDM systems over a geometry-based channel model for shallow UWA channels. We carry out the exact calculation of the ICI power, ambient noise power, and required transmit power, as well as their effects on the performance of UWA-OFDM systems. The signal-to-interference ratio (…
Path Integral approach via Laplace’s method of integration for nonstationary response of nonlinear systems
2019
In this paper the nonstationary response of a class of nonlinear systems subject to broad-band stochastic excitations is examined. A version of the Path Integral (PI) approach is developed for determining the evolution of the response probability density function (PDF). Specifically, the PI approach, utilized for evaluating the response PDF in short time steps based on the Chapman–Kolmogorov equation, is here employed in conjunction with the Laplace’s method of integration. In this manner, an approximate analytical solution of the integral involved in this equation is obtained, thus circumventing the repetitive integrations generally required in the conventional numerical implementation of …
A spatial algorithm to reduce phase wraps from two dimensional signals in fringe projection profilometry
2016
© 2015 Elsevier Ltd. All rights reserved. In this paper, we present a novel algorithm to reduce the number of phase wraps in two dimensional signals in fringe projection profilometry. The technique operates in the spatial domain, and achieves a significant computational saving with regard to existing methods based on frequency shifting. The method works by estimating the modes of the first differences distribution in each axial direction. These are used to generate a tilted plane, which is subtracted from the entire phase map. Finally, the result is re-wrapped to obtain a phase map with fewer wraps. The method may be able to completely eliminate the phase wraps in many cases, or can achieve…
Aalto-1, multi-payload CubeSat: Design, integration and launch
2021
The design, integration, testing, and launch of the first Finnish satellite Aalto-1 is briefly presented in this paper. Aalto-1, a three-unit CubeSat, launched into Sun-synchronous polar orbit at an altitude of approximately 500 km, is operational since June 2017. It carries three experimental payloads: Aalto Spectral Imager (AaSI), Radiation Monitor (RADMON), and Electrostatic Plasma Brake (EPB). AaSI is a hyperspectral imager in visible and near-infrared (NIR) wavelength bands, RADMON is an energetic particle detector and EPB is a de-orbiting technology demonstration payload. The platform was designed to accommodate multiple payloads while ensuring sufficient data, power, radio, mechanica…
Modeling Snow Dynamics Using a Bayesian Network
2015
In this paper we propose a novel snow accumulation and melt model, formulated as a Dynamic Bayesian Network DBN. We encode uncertainty explicitly and train the DBN using Monte Carlo analysis, carried out with a deterministic hydrology model under a wide range of plausible parameter configurations. The trained DBN was tested against field observations of snow water equivalents SWE. The results indicate that our DBN can be used to reason about uncertainty, without doing resampling from the deterministic model. In all brevity, the DBN's ability to reproduce the mean of the observations was similar to what could be obtained with the deterministic hydrology model, but with a more realistic repre…
A risk evaluation framework for the best maintenance strategy: the case of a marine salt manufacture firm
2020
Highlights • This paper proposes a MCDM framework to support risk evaluation for maintenance activities. • The ANP is proposed to select the best maintenance strategy on the basis of real systems’ features. • The ELECTRE III is used to prioritise the main risks related to the interventions of the selected maintenance policy. • The proposed framework is applied to a core subsystem of a real-world marine salt manufacture firm.