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2019 4th International Conference on Intelligent Computing and signal processing, ICSP 2019

作者： Zhou, Jian Hu, Yuting Lian, Hailun Pang, Cong Wang, Huabin Tao, Liang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei AnHui230039 China School of Computer Science and Technology Anhui University Hefei AnHui230601 China

Converting whisper to normal vocalized speech has been a hot research topic in speech signal processing area. A complete and large scale whisper database is a major basis for this task. In this paper, we propose a multimodal whisper database in Chinese mandarin. A total of 103 syllables and 100 sentences were carefully selected. 5 male and 5 female participants pronounced the syllables and sentences in whisper and normal styles respectively, result in 4096 parallel speech utterances and 263, 849 frames of voicing face and lip image sequences. The beginning and ending sample point of each syllable were labeled both for speech signal and voicing face video. The lip region of interest were also extracted and provided in the proposed database. Experiments in various speech conversion tasks in different speech database show the effectiveness of the proposed multimodal whisper speech database. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Database systems

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Simultaneous Prediction of SOH and RUL for Lithium-ion Batteries Using Transferable Knowledge Sharing Network

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IEEE Transactions on Power Electronics 2025年

作者： Zhong, Kai Liu, Zhihao Tian, Jiaqiang Fan, Chao Li, Mince Wang, Yujie Liu, Xinghua Wang, Peng Anhui University Institutes of Physical Science and Information Technology Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Hefei230601 China Anhui University School of Eelectrical Engineering and Automation Anhui230039 China Hefei Comprehensive National Science Center Institute of Energy Hefei230601 China University of Science and Technology of China Department of Automation Hefei230027 China Xi'an University of Technology School of Electrical Engineering Xi'an710048 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore

The state of health (SOH) and remaining useful life (RUL) prediction of lithium-ion batteries are critical for the safe operation and maintenance optimization of electrical systems. However, existing methods face challenges in generalization ability and prediction accuracy, including the limitations of single-task learning for joint SOH and RUL prediction, sensitivity to complex operating conditions, and the impact of cross-domain data distribution differences. To address these challenges, this paper proposes a dual-representation transferable knowledge sharing network (DRTKSN) to predict SOH and RUL for batteries. The proposed algorithm is based on the framework of multi task learning (MTL) and Transfer Learning. By extracting and fusing dual-representation data features, the framework effectively captures the latent patterns of battery aging characteristics. It employs parameter and network structure sharing mechanisms to enhance the adaptability and generalization of cross-domain features. The proposed model achieves information collaboration between SOH and RUL tasks through a shared network, effectively reducing computational costs and improving prediction accuracy. Experimental results demonstrate that the proposed framework exhibits excellent robustness and transferability in complex degradation scenarios, significantly outperforming baseline models. © 1986-2012 IEEE.

关键词： Multi-task learning

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Improved Model-Based Channel Tracking for Underwater Acoustic Communications

Improved Model-Based Channel Tracking for Underwater Acousti...

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Sensor Array and Multichannel signal processing Workshop

作者： Yuxing Wang Jun Tao Le Yang Fei Yu Chunguo Li Xiao Han Key Laboratory of Underwater Acoustic Signal Processing of the Ministry of Education School of Information Science and Engineering Southeast University Nanjing China Department of ECE University of Canterbury Christchurch New Zealand Acoustic Science and Technology Laboratory Harbin Engineering University Harbin China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

For tracking time-varying underwater acoustic (UWA) channels, a state-space model based scheme generally outperforms a direct adaptive method. The success for the former depends on the choice of a proper state transition model as well as accurate estimation of the model parameters. The autoregressive (AR) transition model has proven to be useful and the key is to determine the AR coefficients so as to achieve a good channel tracking performance. In this paper, we revisit the problem of determining the AR coefficients via Yule-Walker equation, for which the required autocorrelations are estimated as an ensemble average of estimated channel impulse responses (CIRs). Different from existing scheme employing least squares (LS) channel estimation, we propose to obtain a sequence of CIR estimations via adaptive schemes. The advantage is twofold: first, complexity reduction is achieved and the saving can be significant for a UWA channel with extensive delay spread; second, improved tracking performance is achieved as the implicit assumption by the LS method that the channel remains constant over a block is not required. We also propose to dynamically update the autocorrelations and AR coefficients as the channel tracking progresses, such that the variation in the channel statistical property can be captured. Both simulations and experimental results verify the performance gain of the proposed model-based channel tracking scheme.

关键词： Adaptation models Correlation Computational modeling Channel estimation Estimation Delays Complexity theory

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Audio Tagging by Cross Filtering Noisy Labels

arXiv

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arXiv 2020年

作者： Zhu, Boqing Xu, Kele Kong, Qiuqiang Wang, Huaimin Peng, Yuxing Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology Changsha410073 China Centre for Vision Speech and Signal Processing University of Surrey GuildfordGU2 7XH United Kingdom

—High quality labeled datasets have allowed deep learning to achieve impressive results on many sound analysis tasks. Yet, it is labor-intensive to accurately annotate large amount of audio data, and the dataset may contain noisy labels in the practical settings. Meanwhile, the deep neural networks are susceptive to those incorrect labeled data because of their outstanding memorization ability. In this paper, we present a novel framework, named CrossFilter, to combat the noisy labels problem for audio tagging. Multiple representations (such as, Logmel and MFCC) are used as the input of our framework for providing more complementary information of the audio. Then, though the cooperation and interaction of two neural networks, we divide the dataset into curated and noisy subsets by incrementally pick out the possibly correctly labeled data from the noisy data. Moreover, our approach leverages the multitask learning on curated and noisy subsets with different loss function to fully utilize the entire dataset. The noisy-robust loss function is employed to alleviate the adverse effects of incorrect labels. On both the audio tagging datasets FSDKaggle2018 and FSDKaggle2019, empirical results demonstrate the performance improvement compared with other competing approaches. On FSDKaggle2018 dataset, our method achieves state-of-the-art performance and even surpasses the ensemble models. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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Rectangular Cavity Slot Array

Rectangular Cavity Slot Array

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International Conference on Microwave and Millimeter Wave technology Proceedings

作者： Jing Jian Huang Xiao Fa Zhang Lin Chen Chang Zhu Nai Chang Yuan State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System National University of Defense Technology Changsha China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

A 5×5 broadside slot array backed by a single cavity containing a mode filter is designed. The resonant slot length is obtained by using a waveguide slot model. The simulated and measured results show that this a...

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Mathematical Modeling of Shear Stress and Direct Shear Test for Compressible Soil: Case of Soil Bordering the Wouri River

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World Journal of Engineering and technology 2021年第3期9卷 385-406页

作者： Michael Soup Teoua Ouagni François Ngapgue Fabien Kenmogne Alain Soup Tewa Kammogne Simon Ngoh Koumi Dschang School of Science and Technology (DSST) Department of Physics Mechanical Unit of Research and Modeling Physical Systems Energy-Mechanic University of Dschang Cameroon Dschang Cameroon Department of Civil Engineering Fotso Victor Institute of Technology University of Dschang Bandjoun Cameroon Department of Civil Engineering Higher Teacher Training College of Technical Education University of Douala Douala Cameroon Laboratory of Condensed Matter Electronics and Signal Processing (LAMACETS) Faculty of Sciences University of Dschang Dschang Cameroon Department Thermal Engineering and Energy Douala University Institute of Technology Douala Cameroon

This paper focuses on the development of the mathematical model of shear stress by direct shear test for compressible soil of the littoral region, which will be a great tool in the hand of geotechnical engineers. The most common use of a shear test is to determine the shear strength which is the maximum shear stress that a material can withstand before the failure occurs. This parameter is useful in many engineering designs such as foundations, roads and retaining walls. We carried out an experimental laboratory test of ten samples of undisturbed soil taken at different points of the border of Wouri river of Cameroon. The samples were collected at different depths and a direct shear test was conducted. The investigations have been performed under constant vertical stresses and constant sample volume with the aim to determine the frictional angle and the cohesion of the compressible soil which are so important to establish the conditions of buildings stability. Special care was taken to derive loading conditions actually existing in the ground and to duplicate them in the laboratory. Given that the buildings constructed in this area are subjected to settlement, landslide, and punch break or shear failure, the cohesion and the frictional angle are determined through the rupture line after assessed the mean values of the shear stress for the considered ten samples. The bearing capacity of the soil, which is the fundamental soil parameter, was calculated. From the laboratory experimental results, the least squared method was used to derive an approximated mathematical model of the shearing stress. Many optimizations methods were then considered to reach the best adjustment.

关键词： Direct Shear Test Normal and Critical Stresses Frictional Angle Bearing Capacity Mathematical Model

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A Imaging Passive Localization Method for Wideband signal Based on SAR 6

A Imaging Passive Localization Method for Wideband Signal Ba...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Wang, Yuqi Sun, Guang-Cai Xiang, Jixiang Xing, Mengdao Guo, Liang Yang, Jun National Laboratory of Radar Signal Processing Xidian University Xi'an China School of Physics and Optoelectronic Engineering Xidian University Xi'an China College of Geomatics Xi'An University of Science and Technology Xi'an China

ISBN: (纸本)9781728129129

A imaging passive localization method for wideband signal is proposed in this paper. By introducing synthetic aperture radar (SAR) imaging method, the location of the signal emitter is directly given in SAR image. The key of this method is to focus unknown wideband data in range and azimuth domain. To focus the data in range domain without signal parameter, a new pulse compress method is proposed by constructing reference signal from raw data. To focus the data in azimuth domain without knowing range, a range-searching azimuth focus method is proposed by constructing azimuth focus functions with different range. Simulation result validate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Synthetic aperture radar

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A New Approach for Optimization Selection of Spaceborne SAR Beam Position Parameters 6

A New Approach for Optimization Selection of Spaceborne SAR ...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Du, Mingang Sun, Guang-Cai Cao, Yandong Xing, Mengdao Guo, Liang Yang, Jun National Laboratory of Radar Signal Processing Xidian University Xi'an China School of Physics and Optoelectronic Engineering Xidian University Xi'an China College of Geomatics Xi'An University of Science and Technology Xi'an China

ISBN: (纸本)9781728129129

In this paper, a new optimized selection method of beam position parameters for spaceborne synthetic aperture radar(SAR) is proposed. Aiming at the difficulty in selecting pulse repeatition frequency (PRF) and observation band width in spaceborne SAR beam position design, this paper deduces the iterative relationship between adjacent beam positions in detail from the spaceborne SAR beam geometry, and proposes an automatic optimization and selection method for beam position parameters. The proposed method meets the principles of PRF restriction and maximum observation band width. The PRF and observation band width of one beam position can be optimized and selected at the same time, and the next beam position parameters can be automatically iteratively selected according to the current selection result. Simulation results validate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Iterative methods

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Multilevel Characteristic Basis Function Method with ACA for Accelerated Solution of Electrically Large Scattering Problems

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Transactions of Nanjing University of Aeronautics and Astronautics 2018年第3期35卷 449-454页

作者： Li Chenlu Sun Yufa Wang Zhonggen Wang Guohua Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University College of Electrical and Information Engineering Anhui University of Science and Technology

The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this *** the conventional MLCBFM based on Foldy-Lax multiple scattering equations,the improvement is only made in the generation of characteristic basis functions(CBFs).However,it does not provide a change in impedance matrix filling and reducing matrix calculation procedure,which is *** reality,all the impedance and reduced matrix of each level of the MLCBFM have low-rank property and can be calculated ***,ACA is used for the efficient generation of two-level CBFs and the fast calculation of reduced matrix in this *** results are given to demonstrate the accuracy and efficiency of the method.

关键词： multilevel characteristic basis function method(MLCBFM) adaptive cross approximation(ACA) characteristic basis functions(CBFs) electromagnetic scattering

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An Overlapping Community Detection Based Multi-Objective Evolutionary Algorithm for Diversified Social Influence Maximization

An Overlapping Community Detection Based Multi-Objective Evo...

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Congress on Evolutionary Computation

作者： Lei Zhang Fengiiao Sun Fan Cheng Haiping Ma Xiaoyan Sun Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China Institutes of Physical Science and Information Technology Anhui University Hefei China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

ISBN: (数字)9781728169293

ISBN: (纸本)9781728169309

Influence maximization refers to selecting a group of nodes from a social network, which obtains the largest influence spread under a cascade model. However, most of the existing works only focused on the influence and ignored the diversity of influenced crowd. Thus, scholars have raised the issue of diversified social influence maximization recently, using the category information of nodes to design diversity indicator and introducing a trade-off parameter to balance the two objectives influence and diversity as one single objective for optimization. In fact, the category information of nodes in the network is usually difficult to be collected, thus the definition of diversity based on nodes' categories is not very general and accurate. In addition, it is very difficult to set the trade-off parameter, especially when there is no prior knowledge in real applications. To this end, we employ overlapping community structure information to design the diversity of nodes without any node's additional (e.g. category) information. Due to the two objectives of influence and diversity may be conflicting, a multi-objective evolutionary algorithm named MOEA-DIM is proposed to optimize the two objectives simultaneously, which does not need to set the tradeoff parameter between the two objectives. In MOEA-DIM, a network reduction strategy based on overlapping community structure is suggested to greatly reduce the search space. In addition, a population initialization strategy based on random walk is designed to accelerate the convergence of the algorithm. Experiments on six real-world datasets show that the proposed algorithm MOEA-DIM has promising performance in terms of both effectiveness and efficiency.

关键词： Optimization Encoding

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