Search results for "LTE"

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

Three-Dimensional Integral-Imaging Display From Calibrated and Depth-Hole Filtered Kinect Information

2016

We exploit the Kinect capacity of picking up a dense depth map, to display static three-dimensional (3D) images with full parallax. This is done by using the IR and RGB camera of the Kinect. From the depth map and RGB information, we are able to obtain an integral image after projecting the information through a virtual pinhole array. The integral image is displayed on our integral-imaging monitor, which provides the observer with horizontal and vertical perspectives of big 3D scenes. But, due to the Kinect depth-acquisition procedure, many depthless regions appear in the captured depth map. These holes spread to the generated integral image, reducing its quality. To solve this drawback we …

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…

JOINT TOPOLOGY LEARNING AND GRAPH SIGNAL RECOVERY VIA KALMAN FILTER IN CAUSAL DATA PROCESSES

2018

In this paper, a joint graph-signal recovery approach is investigated when we have a set of noisy graph signals generated based on a causal graph process. By leveraging the Kalman filter framework, a three steps iterative algorithm is utilized to predict and update signal estimation as well as graph topology learning, called Topological Kalman Filter or TKF. Similar to the regular Kalman filter, we first predict the a posterior signal state based on the prior available data and then this prediction is updated and corrected based on the recently arrived measurement. But contrary to the conventional Kalman filter algorithm, we have no information of the transition matrix and hence we relate t…

2021

Classification approaches that allow to extract logical rules such as decision trees are often considered to be more interpretable than neural networks. Also, logical rules are comparatively easy to verify with any possible input. This is an important part in systems that aim to ensure correct operation of a given model. However, for high-dimensional input data such as images, the individual symbols, i.e. pixels, are not easily interpretable. Therefore, rule-based approaches are not typically used for this kind of high-dimensional data. We introduce the concept of first-order convolutional rules, which are logical rules that can be extracted using a convolutional neural network (CNN), and w…

Food tray sealing fault detection using hyperspectral imaging and PCANet

2020

Abstract Food trays are very common in shops and supermarkets. Fresh food packaged in trays must be correctly sealed to protect the internal atmosphere and avoid contamination or deterioration. Due to the speed of production, it is not possible to have human quality inspection. Thus, automatic fault detection is a must to reach high production volume. This work describes a deep neural network based on Principal Component Analysis Network (PCANet) for food tray sealing fault detection. The input data come from hyperspectral cameras, showing more characteristics than regular industrial cameras or the human eye as they capture the spectral properties for each pixel. The proposed classification…

Wind component estimation for UAS flying in turbulent air

2019

One of the most important problem of autonomous flight for UAS is the wind identification, especially for small scale vehicles. This research focusses on an identification methodology based on the Extended Kalman Filter (EKF). In particular authors focus their attention on.the filter tuning problem. The proposed procedure requires low computational power, so it is very useful for UAS. Besides it allows a robust wind component identification even when, as it is usually, the measurement data set is affected by noticeable noises. (C) 2019 Elsevier Masson SAS. All rights reserved.

Tracking Moving Objects With a Catadioptric Sensor Using Particle Filter

2011

International audience; Visual tracking in video sequences is a widely developed topic in computer vision applications. However, the emergence of panoramic vision using catadioptric sensors has created the need for new approaches in order to track an object in this type of images. Indeed the non-linear resolution and the geometric distortions due to the insertion of the mirror, make tracking in catadioptric images a very challenging task. This paper describes particle filter for tracking moving object over time using a catadioptric sensor. In this work different problems due to the specificities of the catadioptric systems such as geometry are considered. The obtained results demonstrate an…

Performance and feasibility of biotrickling filtration in the control of styrene industrial air emissions

2017

Abstract The performance and feasibility of a pilot unit of biotrickling filter (BTF) for the treatment of industrial emissions polluted by styrene was investigated for one year at a fiber reinforced plastic industrial site. The pilot unit was packed with a structured material with a volume of 0.6 m3. Monitoring results have shown successful treatment of the industrial styrene emissions working at empty bed residence times (EBRT) between 31 and 66 s. The best performance was obtained after 300 days when a more stable biofilm had been developed, obtaining the highest elimination capacity of 18.8 g m−3 h−1 (removal efficiency of 75.6%) working at 31 s of EBRT. In addition, a photocatalytic re…

Rodzinna postpamięć Ślązaków

2017

Family Postmemory of the People of Silesia
 The author suggests a possible use of postmemory to analyse the contemporary family memory of the people of Silesia. Their memoirs about WW2 (such as working for the Wehrmacht, the Red Army invading Silesia, working in labour camps, nationality verification, displacements to Germany, and deportations to Siberia) bear signs of latent memory which is rarely revealed even to the next of kin. Present mainly within the family circle, within the local society, and among friends, these memoirs integrated Silesians and made them a unique community that considers itself a stigmatized minority. This contributed to mythologizing and stereotyping the who…