Search results for "Correlation"
showing 10 items of 2282 documents
Upport vector machines for nonlinear kernel ARMA system identification.
2006
Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA 2k) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based syste…
Modelling and Analysis of Non-Stationary Multipath Fading Channels with Time-Variant Angles of Arrival
2017
In mobile radio channel modelling, it is generally assumed that the angles of arrival (AOAs) are independent of time. This assumption does in general not agree with real-world channels in which the AOAs vary with the position of a moving receiver. In this paper, we first present a mathematical model for the time-variant AOAs. This model serves as the basis for the development of two non-stationary multipath fading channels models. The statistical properties of both channel models are analysed with emphasis on the time-dependent autocorrelation function (ACF), time-dependent mean Doppler shift, time-dependent Doppler spread, and the Wigner-Ville spectrum. It is shown that these characteristi…
Hidden Pursuits: Evaluating Gaze-selection via Pursuits when the Stimuli's Trajectory is Partially Hidden
2018
The idea behind gaze interaction using Pursuits is to leverage the human's smooth pursuit eye movements performed when following moving targets. However, humans can also anticipate where a moving target would reappear if it temporarily hides from their view. In this work, we investigate how well users can select targets using Pursuits in cases where the target's trajectory is partially invisible (HiddenPursuits): e.g., can users select a moving target that temporarily hides behind another object? Although HiddenPursuits was not studied in the context of interaction before, understanding how well users can perform HiddenPursuits presents numerous opportunities, particularly for small interfa…
Efficient and Accurate OTU Clustering with GPU-Based Sequence Alignment and Dynamic Dendrogram Cutting.
2015
De novo clustering is a popular technique to perform taxonomic profiling of a microbial community by grouping 16S rRNA amplicon reads into operational taxonomic units (OTUs). In this work, we introduce a new dendrogram-based OTU clustering pipeline called CRiSPy. The key idea used in CRiSPy to improve clustering accuracy is the application of an anomaly detection technique to obtain a dynamic distance cutoff instead of using the de facto value of 97 percent sequence similarity as in most existing OTU clustering pipelines. This technique works by detecting an abrupt change in the merging heights of a dendrogram. To produce the output dendrograms, CRiSPy employs the OTU hierarchical clusterin…
Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology
2021
[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. In order to characterize the left ventricle, it is necessary to extract its volume. In this work we present a neural network architecture that is capable of directly estimating the left ventricle volume in short axis cine Magnetic Resonance Imaging in the end-diastolic frame and provide a segmentation of the region which is the basis of the volume calculation, thus offering explain-ability to the estimated value. Methods: The network was des…
A novel identification procedure from ambient vibration data
2020
AbstractAmbient vibration modal identification, also known as Operational Modal Analysis, aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures. However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method b…
A Measure of Concurrent Neural Firing Activity Based on Mutual Information
2021
Multiple methods have been developed in an attempt to quantify stimulus-induced neural coordination and to understand internal coordination of neuronal responses by examining the synchronization phenomena in neural discharge patterns. In this work we propose a novel approach to estimate the degree of concomitant firing between two neural units, based on a modified form of mutual information (MI) applied to a two-state representation of the firing activity. The binary profile of each single unit unfolds its discharge activity in time by decomposition into the state of neural quiescence/low activity and state of moderate firing/bursting. Then, the MI computed between the two binary streams is…
Spectrogram analysis of multipath fading channels
2015
The analysis of the Doppler power spectral density (PSD) of measured and simulated data is an important topic in the area of mobile radio channel modelling. In this paper, we estimate the Doppler PSD of multipath fading channels by using the concept of the spectrogram. The spectrogram is a spectral representation that gives insight into how the distribution of the spectral density of a signal changes over time. The multipath fading channel is modelled by a sum-of-cisoids (SOC) process. A closed-form solution is presented for the spectrogram and the corresponding time-dependent autocorrelation function (ACF). The closed-form solutions disclose several unwanted effects that come with the limi…
Recent Advances in Large-scale Structure Statistics
1997
I review the most recent redshift surveys used to probe the large scale structure of the Universe. Then I provide an overview of some of the statistical tools used to describe the galaxy distribution, trying to connect these measures with some of the statistics used in the mainstream of spatial statistics. Special topics include intensity functions, topology, and second-order statistics (2-point correlation function, K-function).
Modelling of non-stationary mobile radio channels using two-dimensional brownian motion processes
2013
The interdisciplinary idea of this paper is to employ a two-dimensional (2D) Brownian motion (BM) process to model non-stationary mobile fading channels. It is assumed that the mobile station (MS) starts moving from a fixed point along a random path in the 2D plane. We model such a moving scenario by a 2D BM process, in which the variance of the process determines the deviation of the MS from its starting point. The propagation area is modelled by a non-centred one-ring scattering model, where the local scatterers are uniformly distributed on a ring centred not necessarily on the MS. The random movement of the MS in the proposed scattering model results in local angles-of-arrival (AOAs) and…