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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Liu, Baohong Chen, Ying Fan, Tanghuai Cooperative Sensing and Intelligent Processing Jiangxi Province Key Laboratory of Water Information Nanchang Institute of Technology Nanchang330099 China School of Noncommissioned Officer Nanchang Institute of Technology Nanchang330099 China

ISBN: (纸本)9781538683392

Rectifier is the core of far field wireless energy harvester (FFWEH) and its performances have imposed serious effects on application of FFWEH system. In the real applications, environmental conditions such as absorption, reflection, multipath fading lead to lots of challenges to harvester development, especially its core rectifier. In the paper, challenges and the relative approach of rectifier development for FFWEH in variation of incident RF power are presented. Firstly, the characteristics of rectifier tightly related to the incident wave power are briefly introduced. Then, Challenges in rectifier design are analyzed in details. Lastly, recent approaches for these challenges are reviewed and analyzed in details. Depended on these effective approaches rectifier can get enhancement of performances to mitigate impacts of environment conditions. © 2018 IEEE.

关键词： Threshold voltage

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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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Maneuvering Target Tracking Based on Multiple-model Multipath Bernoulli Filter

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IOP Conference Series: Materials Science and Engineering 2020年第1期790卷

作者： Yong Qin Yong Liu Kangjie Li Baojuan Zou Baohong Liu School of Information Engineering Nanchang Institute of Technology Nanchang 330099 China Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang 330099 China

Aiming at the problem of maneuvering single target tracking in over the horizon radar system under the clutter environment, a novel multiple-model multipath Bernoulli filter (MM-MPBF) algorithm is proposed. First, the multipath target measurement model is established based on the finite set statistics, and then combining the multiple models method with the multipath Bernoulli filter to deal with the single maneuvering target tracking problem in over the horizon radar system. Finally, the simulation experiment is used to verify the performance of the MM-MPBF algorithm.

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A review of uncertainty quantification in deep learning: Techniques, applications and challenges

arXiv

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arXiv 2020年

作者： Abdar, Moloud Pourpanah, Farhad Hussain, Sadiq Rezazadegan, Dana Liu, Li Ghavamzadeh, Mohammad Fieguth, Paul Cao, Xiaochun Khosravi, Abbas Rajendra Acharya, U. Makarenkov, Vladimir Nahavandi, Saeid Deakin University Australia College of Mathematics and Statistics Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Shenzhen518060 China Dibrugarh University Dibrugarh India Department of Computer Science and Software Engineering Swinburne University of Technology Melbourne Australia Center for Machine Vision and Signal Analysis University of Oulu Oulu Finland Google research United States Department of Systems Design Engineering University of Waterloo Waterloo Canada State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China Department of Electronics and Computer Engineering Ngee Ann Polytechnic Clementi Singapore Department of Computer Science University of Quebec in Montreal MontrealQC Canada

—Uncertainty quantification (UQ) plays a pivotal role in the reduction of uncertainties during both optimization and decision making, applied to solve a variety of real-world applications in science and engineering. Bayesian approximation and ensemble learning techniques are two of the most widely-used UQ methods in the literature. In this regard, researchers have proposed different UQ methods and examined their performance in a variety of applications such as computer vision (e.g., self-driving cars and object detection), image processing (e.g., image restoration), medical image analysis (e.g., medical image classification and segmentation), natural language processing (e.g., text classification, social media texts and recidivism risk-scoring), bioinformatics, etc. This study reviews recent advances in UQ methods used in deep learning, investigates the application of these methods in reinforcement learning, and highlight the fundamental research challenges and directions associated with the UQ field. Copyright © 2020, The Authors. All rights reserved.

关键词： Image segmentation

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Wireless communication using chaotic baseband waveform

arXiv

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arXiv 2019年

作者： Yao, Jun-Liang Sun, Yu-Zhe Ren, Hai-Peng Grebogi, Celso Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China Institute for Complex System and Mathematical Biology University of Aberdeen AB24 3UE United Kingdom

Some new properties of the chaotic signal have been implemented in communication system applications recently. They include: (i) chaos is proven to be the optimal communication waveform in the sense of very simple matched filter being used to achieve maximum signal to noise ratio;(ii) the amount of information contained in a chaotic signal is unaltered by a wireless multipath channel;and (iii) chaos property can be used to resist multipath effect. All these support the application of chaos in a practical communication system. However, due to the broadband property of the chaotic signal, it is very difficult for a practical transducer or antenna to convert such a broadband signal into a signal that would be suitable for practical band-limited wireless channel. Thus, the use of chaos property to improve the performance of conventional communication system without changing the system configuration becomes a critical issue in communication with chaos. In this paper, chaotic baseband waveform generated by a chaotic shaping filter is used to show that this difficulty can be overcome. The generated continuous-time chaotic waveform is proven to be topologically conjugate to a symbolic sequence, allowing the encoding of arbitrary information sequence into the chaotic waveform. A finite impulse response filter is used to replace the impulse control in order to encode information into the chaotic signal, simplifying the algorithm for high speed communication. A wireless communication system is being proposed using the chaotic signal as the baseband waveform, which is compatible with the general wireless communication platform. The matched filter and decoding method, using chaos properties, enhance the communication system performance. The Bit Error Rate (BER) and computational complexity performances of the proposed wireless communication system are analyzed and compared with the conventional wireless systems. The results show that the proposed chaotic baseband waveform of our

关键词： Bit error rate

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Artificial intelligence enhances the performance of chaos-based wireless communication

arXiv

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arXiv 2019年

作者： Ren, Hai-Peng Zhao, Hong-Er Bai, Chao Yin, Hui-Ping Grebogi, Celso Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xian710048 China Institute for Complex Systems and Mathematical Biology University of Aberdeen AB24 3UE United Kingdom

Some new findings for chaos-based wireless communication systems have been identified recently. First, chaos has proven to be the optimal communication waveform because chaotic signals can achieve the maximum signal to noise ratio at receiver with the simplest matched filter. Second, the information transmitted in chaotic signals is not modified by the multipath wireless channel. Third, chaos properties can be used to relief inter-symbol interference (ISI) caused by multipath propagation. Although recent work has reported the method of obtaining the optimal threshold to eliminate the ISI in chaos-based wireless communication, its practical implementation is still a challenge. By knowing the channel parameters and all symbols, especially the future symbol to be transmitted in advance, it is almost an impossible task in the practical communication systems. Owning to Artificial intelligence (AI) recent developments, Convolutional Neural Network (CNN) with deep learning structure is being proposed to predict future symbols based on the received signal, so as to further reduce ISI and obtain better bit error rate (BER) performance as compared to that used the existing sub-optimal threshold. The feature of the method involves predicting the future symbol and obtaining a better threshold suitable for time variant channel. Numerical simulation and experimental results validate our theory and the superiority of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： signal to noise ratio

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processing of Millimeter Wave Airborne Interferometric SAR Data

Processing of Millimeter Wave Airborne Interferometric SAR D...

引用

signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Feng Tian Yuekun Wang Zhibin Wang Zhiqiang Liao Zhiyong Suo Zhenfang Li Wei Yan Jiwei Hu National Key Laboratory of Radar Signal Processing Xidian University Xi'an China Nanjing Research Institute of Electronics Technology Nanjing China Beijing Institute of Spacecraft System Engineering Beijing China Sichuan Aerospace Electronic Equipment Research Institute Sichuan China China Academy of Space Technology Xi'an Brance Xi'an Chinas

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Compared to other wave bands, interferometric synthetic aperture radar (InSAR) system employed millimeter wave equipment is capable of providing finer spatial resolution and higher measurement accuracy with smaller volume and lighter weight. However, the shorter wave length, which is more sensitive to the range error, also brings some problems in SAR/InSAR data processing. In this paper, a complete processing chain is investigated to generate high-precision digital elevation model (DEM) starting from the millimeter wave radar raw data. Experimental results obtained by the proposed approach are presented and discussed with the real measured airborne millimeter wave SAR data.

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Solder joint image adaptive block compressive sensing with convex optimisation and Gini index

Solder joint image adaptive block compressive sensing with c...

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7th International Symposium on Test Automation and Instrumentation, ISTAI 2018

作者： Zhao, Huihuang Wang, Yaonan Zheng, Jinhua Qiao, Zhijun Zhang, Yun Department of Computer Science and Technology College of Computer Science and Technology Hengyang Normal University Hengyang Hunan China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang China Department of Electrical and Engineering College of Electrical and Information Engineering Hunan University Changsha China School of Mathematical and Statistical Sciences University of Texas Rio Grande ValleyTX United States Institute of Radio and TV Technology Communication University of Zhejiang Hangzhou310018 China

This study aims to improve the performance in solder joint image compression and reconstruction. A novel adaptive block compressive sensing with convex optimisation and Gini index (Ad_BCSGB_Gini) methodology for solder joint image compression and reconstruction is proposed. At first, the image is split into square blocks and each block is resized into a row which consists of a new image. Then, the new image is transformed into a sparse signal by an orthogonal basis matrix, and the image reconstruction is handled as a convex optimisation problem. Moreover, a gradient-based method which has fast computational speed is used to reconstruct image. There is a control factor which controls a norm l1 in the optimisation problem. To achieve the best performance, at last, the proposed method adaptively selects the best result by comparing Gini index of the reconstruction results based on different control factor values. Experimental results with different methods indicate that the Ad_BCSGB_Gini method is able to achieve the best performance in quantisation comparison than several classical algorithms, and Ad_BCSGB_Gini has a good robustness. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Convex optimization

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Correction of “A Frequency-Domain Imaging Algorithm for Translational Variant Bistatic Forward-Looking SAR”

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IEEE Transactions on Geoscience and Remote Sensing 2020年第8期58卷 5820-5820页

作者： Haiwen Mei Yachao Li Mengdao Xing Yinghui Quan Chunfeng Wu National Laboratory of Radar Signal Processing Xidian University Xi’an China Collaborative Innovation Center of Information Sensing and Understanding Xidian University Xi’an China Chengdu Aerospace Science and Industry Microelectronics System Research Institute Chengdu China

In [1] , the result of Fig. 13(b) was incorrectly provided. Now, we provide the corrected result, as shown in Fig. 1 .

关键词： Imaging signal processing radar

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SUPERPIXEL-GUIDED SPARSE UNMIXING FOR REMOTELY SENSED HYPERSPECTRAL IMAGERY

SUPERPIXEL-GUIDED SPARSE UNMIXING FOR REMOTELY SENSED HYPERS...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： Shaoquan Zhang Chengzhi Deng Jun Li Shengqian Wang Fan Li Chenguang Xu Antonio Plaza Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang China Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation School of Geography and Planning Sun Yat-sen University Guangzhou China Hyperspectral Computing Laboratory Escuela Politécnica University of Extremadura Cáceres Spain

Sparse representation-based approaches have been successfully applied to remotely sensed hyperspectral image unmixing. In recent years, sparse unmixing techniques have incorporated spatial information into the sparse unmixing model, achieving improved fractional abundance results. Most spatial-based sparse unmixing methods utilize regular-shaped neighborhoods (e.g., a cross or a square window) to characterize the spatial-contextual information around each pixel. However, the spatial characteristics of natural scenes are not always uniform, but vary according to the observed objects. Therefore, assuming uniform spatial neighborhoods may not be consistent with real spatial structures in the scene. Super-pixels offer a good solution to this problem since they can better characterize such spatial structures. Based on this observation, in this paper we develop a new superpixel-guided sparse unmixing (SPGSU) method for hyperspectral scenes. The proposed SPGSU includes the spatial correlation through a superpixel-based technique rather than assuming predefined pixel grids. Each superpixel can be regarded as a small spatial region, whose shape and size can be adaptively changed to accommodate different spatial structures. Our experimental results, conducted using simulated data sets, quantitatively indicate that our newly proposed method produces better results than other advanced spectral unmixing methods.

关键词： Hyperspectral imaging Libraries Shape signal to noise ratio Sensors

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