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Data processing Methods for Mobile Indoor Navigation 2

Data Processing Methods for Mobile Indoor Navigation

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2nd IEEE international conference on Data Stream Mining and processing (DSMP)

作者： Roienko, Alexey Chervoniak, Yevhen Sirenko, Feliks Gorovyi, Ievgen IT Jim Kharkov Ukraine

ISBN: (纸本)9781538628744

The competition on the world market of smartphones and tablets between the acknowledged leaders on one side and the numerous newcomers on the other makes them all look for new solutions that open additional opportunities for the developers and customers without the growth of the price. The progress with new opportunities turns possible when it happens simultaneously in the software and the hardware. The brightest one example of the above statement can be observed for the sensors of mobile devices. It is totally impossible to imagine modern smart devices having no sensors, as the progress of last decade (SLAM, face ID, OCR, pattern recognition etc.) was achieved thanks to considerable improvements of sensors and the algorithms for their processing. The paper addresses the questions of characteristics analysis of such mobile sensors as accelerometer, magnetometer and gyroscope from the point of view of their application in indoor navigation field. signals of BLE beacons and their processing methods are investigated as well. The sensor fusion task is briefly discussed and several practical examples are given.

关键词： signal processing sensor fusion indoor navigation BLE navigation IMU navigation

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Interferometric-processing Based Small Space Debris Imaging 2nd

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2nd international conference on machine learning and Intelligent Communications, MLICOM 2017

作者： Sun, Yuxue Luo, Ying Zhang, Song Institute of Information and Navigation Air Force Engineering University Xi’an710077 China Natural Laboratory of Radar Signal Processing Xidian University Xi’an710077 China Unit 95980 of the People’s Liberation Army Xiangyang441000 China

ISBN: (纸本)9783319734460

The detection and recognition of small space debris is an important task for space security. This paper proposed an interferometric-processing based imaging method for small space debris. First, based on L-shaped three antennas system, the signal model for interferometric imaging is established. Then aiming at the fact that the size of some space debris is smaller than range resolution, time-frequency analysis is adopted to separate echoes of different scatterers. The mechanism of time-frequency analysis for echo from three antennas is deduced in detail. It is proved that the phase for interferometric processing is reserved in the process of time-frequency analysis. Finally through interferometric processing, the positions and image of scatterers can be reconstructed. Simulations verify the validity of the proposed method. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Radar imaging

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On the Equivalence between AR Family Time Series Models and Fuzzy Models in signal processing 2

On the Equivalence between AR Family Time Series Models and ...

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2nd IEEE international conference on Data Stream Mining and processing (DSMP)

作者： Walaszek-Babiszewska, Anna Rydel, Marek Kashpruk, Nataliia Opole Univ Technol Dept Comp Sci Opole Poland

ISBN: (纸本)9781538628744

In the paper an advanced analysis of the relationships between statistical Autoregressive (AR) type models and fuzzy models have been presented. The examined family of AR type models includes Autoregressive models of order p, AR(p), Threshold AR (TAR) as well as Smooth Transition Autoregressive (STAR) models. On the other hand, fuzzy models representing different approach, characteristic for Computational Intelligence technics, have been tested for time series analysis and forecasting. The data have been taken from financial market. The research can enrich knowledge which is useful for experts using both approaches to modelling.

关键词： Biological system modeling Autoregressive processes Computational modeling Mathematical model Analytical models Time series analysis Data models

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2nd international conference on Soft Computing Systems, ICSCS 2018

2nd International Conference on Soft Computing Systems, ICSC...

引用

2nd international conference on Soft Computing Systems, ICSCS 2018

ISBN: (纸本)9789811319358

The proceedings contain 87 papers. The special focus in this conference is on Soft Computing Systems. The topics include: Ultrasonic signal Modelling and Parameter Estimation: A Comparative Study Using Optimization Algorithms;a Histogram Based Watermarking for Videos and Images with High Security;enhanced Empirical Wavelet Transform for Denoising of Fundus Images;kernelised Clustering Algorithms Fused with Firefly and Fuzzy Firefly Algorithms for Image Segmentation;performance Analysis of Wavelet Transform Based Copy Move Forgery Detection;high Resolution 3D Image in Marine Exploration Using Neural Networks - A Survey;ship Intrusion Detection System - A Review of the State of the Art;Novel Work of Diagnosis of Liver Cancer Using Tree Classifier on Liver Cancer Dataset (BUPA Liver Disorder);Performance Analysis and Error Evaluation Towards the Liver Cancer Diagnosis Using Lazy Classifiers for ILPD;a Weight Based Approach for Emotion Recognition from Speech: An Analysis Using South Indian Languages;exploring Structure Oriented Feature Tag Weighting Algorithm for Web Documents Identification;MQMS - An Improved Priority Scheduling Model for Body Area Network Enabled M-Health Data Transfer;data Compression Using Content Addressable Memories;heart Block Recognition Using Image processing and Back Propagation Neural Networks;design and Development of Laplacian Pyramid Combined with Bilateral Filtering Based Image Denoising;diabetes Detection Using Deep Neural Network;Multi-label Classification of Big NCDC Weather Data Using Deep learning Model;object Recognition Through Smartphone Using Deep learning Techniques;hot Spot Identification Using Kernel Density Estimation for Serial Crime Detection;analysis of Scheduling Algorithms in Hadoop;smart Transportation for Smart Cities.

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Bioinspired Approaches to the Selection and processing of Video Information 2

Bioinspired Approaches to the Selection and Processing of Vi...

引用

2nd IEEE international conference on Data Stream Mining and processing (DSMP)

作者： Boyun, Vitaliy VM Glushkov Inst Cybernet NASU Dept Intelligent Real Time Video Syst Kiev Ukraine

ISBN: (纸本)9781538628744

Significant expansion of the range of applications of real-time video systems requires further improvement in their productivity, efficiency and intelligence. Therefore, researchers are increasingly turning to the human eye analyzer as a prototype to create more sophisticated systems of technical vision. The paper proposes a number of approaches and methods for the selection and processing of video information inspired by the human visual analyzer. In particular: the method of hierarchical selective perception of video information;dynamic models of processes for finding objects, tracking them, panning the scene and the mechanisms of attention and allocation of the essence, which, by managing the parameters of reading information from a video sensor, provide reading of a part of the image relevant to the task;information measure of the dynamic image (6-entropy), which characterizes its spatial frequencies and is an effective information feature for the search and recognition of objects;methods of expanding the dynamic range of perception of brightness;the principles of circular organization neurons of the central fovea, which provide increased contrast and the allocation of informative features;circular organization of the retinal neurons with a sumation of signal sticks that contribute to increased sensitivity in conditions of insufficient lighting;specialization of neurons and organization multilayer neural network.

关键词： video system human visual analyzer bioinspired approaches relevant information neural network

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Adaptive Mainlobe Interference Suppression in Sparse Distributed Array Radar Based on Synthetic Wideband signal 2nd

引用

2nd international conference on machine learning and Intelligent Communications, MLICOM 2017

作者： Luo, Jian Zhang, Honggang Song, Yuanyuan Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9783319734460

This paper proposes a mainlobe interference suppression method in distributed array radar (DAR) based on stepped frequency synthetic wideband signal. Due to the equivalent large aperture of DAR, it is possible to cancel the mainlobe interference without target signal suppression. The applying of stepped frequency synthetic wideband signal can avoid the different time delays arriving at each array compared with the traditional instantaneous wideband Chirp (linear frequency modulation) signal. Moreover, it can reduce the computational complexity. This method employs the narrowband adaptive processing to each sub-pulse of the stepped frequency signal, and then synthesizes the high resolution range profile (HRRP). As a result, mainlobe interference suppression under wideband signal is accomplished. Mainlobe interference suppression experiment is carried out by using an S-band experimental radar system, an S-band noise jammer and a target simulator. The measured data is processed employing the proposed method, and the result verifies the effectiveness of this algorithm. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Beamforming

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Predictive analytics in healthcare system using deep learning approach 1

Predictive analytics in healthcare system using deep learnin...

引用

1st international conference of Computer Science and Renewable Energies, ICCSRE 2018

作者： Lahlali, Salma Ammoumou, Abdelkarim Industrial Engineering Signal Processing and Logistic Laboratory FSAC Hassan 2nd University Casablanca Morocco

ISBN: (纸本)9789897584312

During centuries, and since the appearance of science, the world of healthcare has known a noticeable positive progress. Not only on the researches and inventions term, but also on the intention’s term. The first aim was to save people’s lives and heal patients, from the illnesses which was known back then. After a period, and thanks to the improvement that was known in the field of both science & research, scientists level up to another aim which is preventing. This means, that they were looking for solutions by which doctors will be able to predict a possible disease infection, thus the possibility to prevent an exposure to a disease was being possible. Therefore, saving people’s lives had a new road which needed to be developed with the cooperation of other domains, so a system can be put into action to realize this new mission. The purpose of this article, is to present a system which can predict a possible illness as well as suggest the adequate treatment for the patient’s case. This includes discussing the system’s main objectives and characteristics, in addition to describing its architecture main layers. Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Diseases

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learning Visual Odometry for Unmanned Aerial Vehicles 2

Learning Visual Odometry for Unmanned Aerial Vehicles

引用

2nd IEEE international conference on signal and Image processing (ICSIP)

作者： Wan, Kong-Wah Li, Zhengguo Yau, Wei-Yun Inst Infocomm Res 1 Fusionopolis Way Singapore 138632 Singapore

ISBN: (纸本)9781538609699

We describe a method to learn the flight dynamics of an unmanned aerial vehicle (UAV). This follows the recent trend to adopt a learning approach to Visual Odometry (VO). Our novelty is the inclusion of a module to compensate for the roll pitch angular motion of the UAV due to body vibration. This is a significant deviation from most existing works that are applied to land vehicles. We empirically verify our results on real flight data, showing that after compensating for angular vibration, the ego-motion of the UAV can be robustly estimated even by using simple regression tools. This enables the advantages of learning based VO to be within reach of the UAV community.

关键词： visual odometry machine learning

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Sparse Representation Based SAR Imaging Using Combined Dictionary 2nd

引用

2nd international conference on machine learning and Intelligent Communications, MLICOM 2017

作者： Xu, Han-Yang Zhou, Feng School of Electronic Engineering Xidian University Xi’an710071 China National Lab of Radar Signal Processing Xidian University Xi’an710071 China

ISBN: (纸本)9783319734460

Sparse representation (SR)-based SAR imaging has shown its superior capability in high-resolution image formation. For SR-based SAR imaging task, a key challenge is how to choose a proper dictionary that can effectively represent the magnitude of the complex-valued scattering field. In this paper, we present a combined dictionary that simultaneously enhances multiple types of scattering mechanism. Trained by different kinds of SAR image patches with either strong point scatterers or smooth regions, the dictionary can represent both point-scattering and spatially distributed scenes sparsely. Finally, the SAR image is obtained by solving a joint optimization problem over the combined representation of the magnitude and phase of the observed scene. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Synthetic aperture radar

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Pixel Normalization from Numeric Data as Input to Neural Networks For machine learning and Image processing 2

Pixel Normalization from Numeric Data as Input to Neural Net...

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2nd IEEE international conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Sane, Parth Agrawal, Ravindra Univ Mumbai Dept Comp Engn SIES GST Bombay Maharashtra India

ISBN: (纸本)9781509044429

Text to image transformation for input to neural networks requires intermediate steps. This paper attempts to present a new approach to pixel normalization so as to convert textual data into image, suitable as input for neural networks. This method can be further improved by its Graphics processing Unit (GPU) implementation to provide significant speedup in computational time.

关键词： Data science image processing neural networks pixel normalization

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