Search results for "linear"
showing 10 items of 7165 documents
Improving IEEE 802.11 Performance in Chain Topologies through Distributed Polling and Network Coding
2009
Wireless multi-hop networks often rely on the use of IEEE 802.11 technology. Despite of the robustness of the IEEE 802.11 Distributed Coordination Function (DCF) for working in various network scenarios, it has been proven that critical inefficiencies can arise in the case of multi-hop packet forwarding. In this paper, we propose a MAC scheme, based on the virtualization of the Point Coordination Function, optimized for working on chain topologies with bidirectional traffic flows. Our scheme is based on a token-like access mechanism coupled with network coding. The basic idea is the use of multiple Point Coordinators (PCs) along the node chain, which are elected by passing special token fra…
Nonlinear radial-harmonic correlation using binary decomposition for scale-invariant pattern recognition
2003
We introduce a new scale-invariant pattern-recognition method that uses nonlinear correlation. We applied several common linear correlations to images decomposed into disjoint binary images, which is very discriminant even when the target is embedded in strong noise. We combine our sliced orthogonal nonlinear generalized correlation method and the radial-harmonic expansion in order to achieve scale-invariant pattern recognition. The information from a radial harmonic for each binary slice of the reference object is combined with binary slices of the target. The method avoids the time-consuming process of finding expansion centers for the radial harmonics. The stability of the correlation pe…
Visible-NIR reflectance spectroscopy and manifold learning methods applied to the detection of fungal infections on citrus fruit
2015
Abstract The development of systems for automatically detecting decay in citrus fruit during quality control is still a challenge for the citrus industry. The feasibility of reflectance spectroscopy in the visible and near infrared (NIR) regions was evaluated for the automatic detection of the early symptoms of decay caused by Penicillium digitatum fungus in citrus fruit. Reflectance spectra of sound and decaying surface parts of mandarins cv. ‘Clemenvilla’ were acquired in two different spectral regions, from 650 nm to 1050 nm (visible–NIR) and from 1000 nm to 1700 nm (NIR), pointing to significant differences in spectra between sound and decaying skin for both spectral ranges. Three diffe…
Development of a thermodesorption sensor system for the detection of residual solvents in packaging materials
2004
Application specific sensor systems (formerly electronic noses) use static headspace for the volatile generation from condensed phase samples. This extraction method is very simple to implement, but suffers many drawbacks, i.e. in terms of efficiency or sensitivity to partitioning and is very time-consuming. To circumvent these problems, we developed a new method using dynamic extraction of volatiles (stripping). Although this method is known for GC (gas chromatography), the utilization of direct thermal desorption (DTD) in conjunction with gas sensors is quite novel. The unhandy cold trapping step can be avoided by a software integration of the instantaneous volatile concentration over the…
Nonlinear data description with Principal Polynomial Analysis
2012
Principal Component Analysis (PCA) has been widely used for manifold description and dimensionality reduction. Performance of PCA is however hampered when data exhibits nonlinear feature relations. In this work, we propose a new framework for manifold learning based on the use of a sequence of Principal Polynomials that capture the eventually nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) is shown to generalize PCA. Unlike recently proposed nonlinear methods (e.g. spectral/kernel methods and projection pursuit techniques, neural networks), PPA features are easily interpretable and the method leads to a fully invertible transform, which is a desirable property…
Análisis tiempo-frecuencia de la fibrilación ventricular. Estudio experimental
2006
Introduction and objectives. The analysis of frequency variability during ventricular fibrillation has yielded inconsistent results. We used an experimental model of ventricular fibrillation, with a short timescale, to analyze variations in frequency and their associated spatial distribution. Methods. Epicardial recordings of ventricular fibrillation were made in 10 perfused isolated rabbit heart preparations using a multiple electrode system (i.e., 240 unipolar electrodes). Both spectral and time-frequency analysis were used to derive the dominant frequency in the anterolateral wall of the left ventricle. Results. Linear regression analysis showed that there was a good correlation between …
WiHAR : From Wi-Fi Channel State Information to Unobtrusive Human Activity Recognition
2020
A robust and unobtrusive human activity recognition system is essential to a multitude of applications, such as health care, active assisted living, robotics, sports, and tele-immersion. Existing well-performing activity recognition methods are either vision- or wearable sensor-based. However, they are not fully passive. In this paper, we develop WiHAR—an unobtrusive Wi-Fi-based activity recognition system. WiHAR uses the Wi-Fi network interface card to capture the channel state information (CSI) data. These CSI data are effectively processed, and then amplitude and phase information is used to obtain the spectrogram. In the subsequent step, the time-variant mean Doppler shift (MDS) caused …
Text Classification Using Novel “Anti-Bayesian” Techniques
2015
This paper presents a non-traditional “Anti-Bayesian” solution for the traditional Text Classification (TC) problem. Historically, all the recorded TC schemes work using the fundamental paradigm that once the statistical features are inferred from the syntactic/semantic indicators, the classifiers themselves are the well-established statistical ones. In this paper, we shall demonstrate that by virtue of the skewed distributions of the features, one could advantageously work with information latent in certain “non-central” quantiles (i.e., those distant from the mean) of the distributions. We, indeed, demonstrate that such classifiers exist and are attainable, and show that the design and im…
Interlacing multiplexing techniques for optical morphological correlation
2006
We propose a novel approach to implement nonlinear morphological correlation. Previous implementation was based on a time sequential approach that consists on displaying different binary image decomposition in a joint transform correlator adding each joint power spectra sequentially. A second Fourier transformation of the sum of joint power spectra gives the correlation output. In this paper, we propose to interlace the different binary images into one single distribution. Then, we introduce the distribution in a conventional joint transform correlator. The correlation output gives the morphological correlation at a specific location. The advantage is important considering that no sequentia…