Search results for "IPA"
showing 10 items of 5795 documents
Atrial activity extraction for atrial fibrillation analysis using blind source separation.
2004
This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA …
Wi-Sense: a passive human activity recognition system using Wi-Fi and convolutional neural network and its integration in health information systems
2021
AbstractA human activity recognition (HAR) system acts as the backbone of many human-centric applications, such as active assisted living and in-home monitoring for elderly and physically impaired people. Although existing Wi-Fi-based human activity recognition methods report good results, their performance is affected by the changes in the ambient environment. In this work, we present Wi-Sense—a human activity recognition system that uses a convolutional neural network (CNN) to recognize human activities based on the environment-independent fingerprints extracted from the Wi-Fi channel state information (CSI). First, Wi-Sense captures the CSI by using a standard Wi-Fi network interface car…
Feature selection with Ant Colony Optimization and its applications for pattern recognition in space imagery
2016
This paper presents a feature selection (FS) algorithm using Ant Colony Optimization (ACO). It is inspired by the particular behavior of real ants, namely by the fact that they are capable of finding the shortest path between a food source and the nest. There are considered two ACO-FS model applications for pattern recognition in remote sensing imagery: ACO Band Selection (ACO-BS) and ACO Training Label Purification (ACO-TLP). The ACO-BS reduces dimensionality of an input multispectral image data by selecting the “best” subset of bands to accomplish the classification task. The ACO-TLP selects the most informative training samples from a given set of labeled vectors in order to optimize the…
A non-stationary multipath fading channel model incorporating the effect of velocity variations of the mobile station
2014
A standard assumption in mobile fading channel modelling is that the mobile station (MS) moves along a straight line with constant speed. In practice, this assumption is violated in most propagation scenarios. For the development of more realistic channel models, it is therefore important to relax this restriction by allowing the MS to change its velocity. In this paper, we study the effect of velocity changes on the statistical properties of multipath fading channels. Expressions will be derived for the local autocorrelation function (ACF), the Wigner-Ville spectrum, the average Doppler shift, and the Doppler spread. Our findings show that a variation of the speed and/or the direction of t…
Reduction of the number of spectral bands in Landsat images: a comparison of linear and nonlinear methods
2006
We describe some applications of linear and nonlinear pro- jection methods in order to reduce the number of spectral bands in Land- sat multispectral images. The nonlinear method is curvilinear component analysis CCA, and we propose an adapted optimization of it for image processing, based on the use of principal-component analysis PCA, a linear method. The principle of CCA consists in reproducing the topol- ogy of the original space projection points in a reduced subspace, keep- ing the maximum of information. Our conclusions are: CCA is an im- provement for dimension reduction of multispectral images; CCA is really a nonlinear extension of PCA; CCA optimization through PCA called CCAinitP…
Comparing ELM Against MLP for Electrical Power Prediction in Buildings
2015
The study of energy efficiency in buildings is an active field of research. Modelling and predicting energy related magnitudes leads to analyse electric power consumption and can achieve economical benefits. In this study, two machine learning techniques are applied to predict active power in buildings. The real data acquired corresponds to time, environmental and electrical data of 30 buildings belonging to the University of Leon (Spain). Firstly, we segmented buildings in terms of their energy consumption using principal component analysis. Afterwards we applied ELM and MLP methods to compare their performance. Models were studied for different variable selections. Our analysis shows that…
Fast Image Mosaicing for Panoramic Face Recognition
2006
In this article, we present some development results of a system that performs mosaicing (or mosaicking) of panoramic faces. Our objective is to study the feasibility of panoramic face construction in real-time. To do so, we built a simple acquisition system composed of 5 standard cameras which, together, can take simultaneously 5 views of a face at different angles. Then, we chose an easily hardware-achievable algorithm, consisting of successive linear transformations, in order to compose a panoramic face from these 5 views. The method has been tested on a relatively large number of faces. In order to validate our system of panoramic face mosaicing, we also conducted a preliminary study on…
Real-Time Human Pose Estimation from Body-Scanned Point Clouds
2015
International audience; This paper presents a novel approach to estimate the human pose from a body-scanned point cloud. To do so, a predefined skeleton model is first initialized according to both the skeleton base point and its torso limb obtained by Principal Component Analysis (PCA). Then, the body parts are iteratively clustered and the skeleton limb fitting is performed, based on Expectation Maximization (EM). The human pose is given by the location of each skeletal node in the fitted skeleton model. Experimental results show the ability of the method to estimate the human pose from multiple point cloud video sequences representing the external surface of a scanned human body; being r…
Performance evaluation of sum-of-cisoids Rice/Rayleigh fading channel simulators with respect to the bit error probability
2014
Sum-of-cisoids (SOC) processes provide an important framework for the modeling and simulation of multipath fading channels. In this paper, we analyze the performance of SOC Rice/Rayleigh narrowband fading channel simulators with respect to the bit error probability (BEP) of quadrature phase shift keying (QPSK) and differential phase shift keying (DPSK) systems with both coherent and noncoherent demodulation. For the BEP of coherent QPSK and DPSK, exact analytical expressions are derived, which provide insight into the influence of the number of propagation paths and the path gains on the system performance. It will be shown that at least 10 multipath components are required to guarantee tha…
Keynote talk 3: From basics to advanced modelling and simulation techniques for mobile radio channels
2011
From the earliest beginnings of mobile communications to the present time, there has always been a high demand for realistic mobile radio channel models. This demand is driven by the fact that channel models are indispensable for the performance evaluation, parameter optimisation, and test of mobile communication systems. Channel modelling and simulation techniques are therefore of great importance for electronics and telecommunication engineers who are involved in the development of present and future mobile communication systems. This presentation will start with a review of the basic principles of mobile radio channel modelling and gradually moves to more advanced modelling and simulatio…