Search results for "Signal"
showing 10 items of 6924 documents
Data-based modeling and estimation of vehicle crash processes in frontal fixed-barrier crashes
2017
Abstract As a complex process, vehicle crash is challenging to be described and estimated mathematically. Although different mathematical models are developed, it is still difficult to balance the complexity of models and the performance of estimation. The aim of this work is to propose a novel scheme to model and estimate the processes of vehicle-barrier frontal crashes. In this work, a piecewise model structure is predefined to represent the accelerations of vehicle in frontal crashes. Each segment in the model is corresponding to the energy absorbing component in the crashworthiness structure. With the help of Ensemble Empirical Mode Decomposition (EEMD), a robust scheme is proposed for …
Regularized LMS methods for baseline wandering removal in wearable ECG devices
2016
The acquisition of electrocardiogram (ECG) signals by means of light and reduced size devices can be usefully exploited in several health-care applications, e.g., in remote monitoring of patients. ECG signals, however, are affected by several artifacts due to noise and other disturbances. One of the major ECG degradation is represented by the baseline wandering (BW), a slowly varying change of the signal trend. Several BW removal algorithms have been proposed into the literature, even though their complexity often hinders their implementation into wearable devices characterized by limited computational and memory resources. In this study, we formalize the BW removal problem as a mean-square…
Central catadioptric image processing with geodesic metric
2011
International audience; Because of the distortions produced by the insertion of a mirror, catadioptric images cannot be processed similarly to classical perspective images. Now, although the equivalence between such images and spherical images is well known, the use of spherical harmonic analysis often leads to image processing methods which are more difficult to implement. In this paper, we propose to define catadioptric image processing from the geodesic metric on the unitary sphere. We show that this definition allows to adapt very simply classical image processing methods. We focus more particularly on image gradient estimation, interest point detection, and matching. More generally, th…
Graph Filtering of Time-Varying Signals over Asymmetric Wireless Sensor Networks
2019
In many applications involving wireless sensor networks (WSNs), the observed data can be modeled as signals defined over graphs. As a consequence, an increasing interest has been witnessed to develop new methods to analyze graph signals, leading to the emergence of the field of Graph Signal Processing. One of the most important processing tools in this field is graph filters, which can be easily implemented distributedly over networks by means of cooperation among the nodes. Most of previous works related to graph filters assume the same connection probability in both link directions when transmitting an information between two neighboring nodes. This assumption is not realistic in practice…
A Geometrical Approach for Vision Based Attitude and Altitude Estimation for UAVs in Dark Environments
2012
International audience; This paper presents a single camera and laser system dedicated to the realtime estimation of attitude and altitude for unmanned aerial vehicles (UAV) under low illumination conditions to dark environments. The fisheye camera allows to cover a large field of view (FOV). The approach, close to structured light systems, uses the geometrical information obtained by the projection of a laser circle onto the ground plane and perceived by the camera. We propose some experiments based on simulated data and real sequences. The results show good agreement with the ground truth values from the commercial sensors in terms of its accuracy and correctness. The results also prove i…
Using an Adaptive High-Gain Extended Kalman Filter With a Car Efficiency Model
2010
The authors apply the Adaptive High-Gain Extended Kalman Filter (AEKF) to the problem of estimating engine efficiency with data gathered from normal driving. The AEKF is an extension of the traditional Kalman Filter that allows the filter to be reactive to perturbations without sacrificing noise filtering. An observability normal form of the engine efficiency model is developed for the AEKF. The continuous-discrete AEKF is presented along with strategies for dealing with asynchronous data. Empiric test results are presented and contrasted with EKF-derived results.Copyright © 2010 by ASME
K-nearest neighbor driving active contours to delineate biological tumor volumes
2019
Abstract An algorithm for tumor delineation in positron emission tomography (PET) is presented. Segmentation is achieved by a local active contour algorithm, integrated and optimized with the k-nearest neighbor (KNN) classification method, which takes advantage of the stratified k-fold cross-validation strategy. The proposed approach is evaluated considering the delineation of cancers located in different body districts (i.e. brain, head and neck, and lung), and considering different PET radioactive tracers. Data are pre-processed in order to be expressed in terms of standardized uptake value, the most widely used PET quantification index. The algorithm uses an initial, operator selected re…
Fault detection for nonlinear networked systems based on quantization and dropout compensation: An interval type-2 fuzzy-model method
2016
Abstract This paper investigates the problem of filter-based fault detection for a class of nonlinear networked systems subject to parameter uncertainties in the framework of the interval type-2 (IT2) T–S fuzzy model-based approach. The Bernoulli random distribution process and logarithm quantizer are used to describe the measurement loss and signals quantization, respectively. In the framework of the IT2 T–S fuzzy model, the parameter uncertainty is handled by the membership functions with lower and upper bounds. A novel IT2 fault detection filter is designed to guarantee the residual system to be stochastically stable and satisfy the predefined H ∞ performance. It should be mentioned that…
Contactless generation of cavitation in high temperature liquid metals and its impact on particle dispersion in solidified iron and steel samples
2021
Abstract A recently developed method for the contactless magnetic generation of cavitation is demonstrated for high-melting-point metals. The approach is based on the floating-zone technique, which is truly contactless and crucible-free as it uses electromagnetic forces. Using this method, ultra-high-temperature ceramic particles, such as TiN, TiB2 and TiC, are admixed in liquid iron and 316L steel. The dispersion and particle refinement caused by cavitation treatment during melting and solidification are investigated. Magnetic fields up to 8 T that correspond to pressure oscillation amplitude of 0.83 MPa are used. The signal emitted by the collapsing bubbles is captured and visualized for …
Sampled Fictitious Play on Networks
2019
We formulate and solve the problem of optimizing the structure of an information propagation network between multiple agents. In a given space of interests (e.g., information on certain targets), each agent is defined by a vector of their desirable information, called filter, and a vector of available information, called source. The agents seek to build a directed network that maximizes the value of the desirable source-information that reaches each agent having been filtered en route, less the expense that each agent incurs in filtering any information of no interest to them. We frame this optimization problem as a game of common interest, where the Nash equilibria can be attained as limit…