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Science China(Information Sciences) 2024年第6期67卷 328-341页

作者： Xian-Ming ZHANG Qing-Long HAN Bao-Lin ZHANG Xiaohua GE Dawei ZHANG School of Science Computingand Engineering TechnologiesSwinburne University of Technology College of Automation and electronic engineering Qingdao University of Science & Technology School of Mathematics Shandong University

This paper is concerned with event-triggered H∞control of sampled-data systems. Its novelties lie in three aspects:（i） A novel accumulated-state-error-based event-triggered scheme is introduced by comparing the integral of the state error from tk to t with the system state sampled at tk. This condition works well due to the fact that the so-called Zeno behaviour does not occur.（ii） A novel Lyapunov functional is constructed to establish a criterion to ensure some certain H∞performance of the closed-loop system. This Lyapunov functional is dependent on the integral of the state error involved in the event-triggered scheme.（iii） Under the event-triggered sampling scheme, suitable state-feedback controllers can be designed rather than be given a priori. Moreover, a self-triggered implementation of the proposed event-triggered sampling scheme is presented as well. Finally, a batch reactor model and an inverted pendulum system are given to demonstrate the effectiveness of the proposed method.

关键词： event-triggered sampling self-triggered implementation $H_\infty$ control looped-functional

A novel DPSS filter optimization scheme to reduce the intrinsic interference of FBMC-QAM systems

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High Technology Letters 2024年第1期30卷 68-74页

作者：董琪阳 MA Tianming JIN Jie WU Zhong School of Electrical and electronic engineering Shanghai University of Engineering ScienceShanghai 201620P.R.China

In order to reduce the intrinsic interference of the filter bank multicarrier-quadrature amplitude modulation(FBMC-QAM)system,a novel filter optimization scheme based on discrete prolate spheroidal sequences(DPSS)is ***,a prototype filter function based on DPSS is designed,since the eigenvalue can be used as an indicator of the energy concentration of DPSS,so a threshold is set,and the sequence with the most concentrated energy is selected under the threshold,that is,the sequence with the eigenvalue higher than the threshold,and the prototype filter function is rewritten as a weighted sum function of multiple *** the energy constraints of the filter,the relationship between the eigenvectors and the intrinsic interference function is established,and the function problem is transformed into an optimization problem for the weighted *** the interior point method,the most suitable weight is found to obtain the minimum intrinsic interference *** analysis and simulation results show that compared with the prototype filters such as Type1 and CaseC,the DPSS filter applying the proposed optimization algorithm can effectively suppress the intrinsic interference of the system and obtain a better bit error rate(BER)performance.

关键词： filter bank multicarrier-quadrature amplitude modulation(FBMC-QAM) intrinsic interference discrete prolate spheroidal sequences(DPSS) interior point method

Wigner function of optical cumulant operator and its dissipation in thermo-entangled state representation

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Chinese Physics B 2024年第6期33卷 205-210页

作者：张科李兰兰范洪义 School of electronic engineering Huainan Normal UniversityHuainan 232038China Department of Material Science and engineering University of Science and Technology of ChinaHefei 230026China

To conveniently calculate the Wigner function of the optical cumulant operator and its dissipation evolution in a thermal environment, in this paper, the thermo-entangled state representation is introduced to derive the general evolution formula of the Wigner function, and its relation to Weyl correspondence is also discussed. The method of integration within the ordered product of operators is essential to our discussion.

关键词： Wigner function optical cumulant operator dissipation evolution thermo-entangled state representation integration within ordered product of operators

A Review of NILM Applications with Machine Learning Approaches

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Computers, Materials & Continua 2024年第5期79卷 2971-2989页

作者： Maheesha Dhashantha Silva Qi Liu School of electronic and Information engineering Nanjing University of Information Science and TechnologyNanjing210044China

In recent years,Non-Intrusive LoadMonitoring (NILM) has become an emerging approach that provides affordableenergy management solutions using aggregated load obtained from a single smart meter in the power ***, by integrating Machine Learning (ML), NILM can efficiently use electrical energy and offer less ofa burden for the energy monitoring process. However, conducted research works have limitations for real-timeimplementation due to the practical issues. This paper aims to identify the contribution of ML approaches todeveloping a reliable Energy Management (EM) solution with NILM. Firstly, phases of the NILM are discussed,along with the research works that have been conducted in the domain. Secondly, the contribution of machinelearning approaches in three aspects is discussed: Supervised learning, unsupervised learning, and *** highlights the limitations in the applicability of ML approaches in the field. Then, the challenges in the realtimeimplementation are concerned with six use cases: Difficulty in recognizing multiple loads at a given time,cost of running the NILM system, lack of universal framework for appliance detection, anomaly detection andnew appliance identification, and complexity of the electricity loads and real-time demand side ***, options for selecting an approach for an efficientNILMframework are suggested. Finally, suggestionsare provided for future research directions.

关键词： Non-intrusive load monitoring transfer learning machine learning feature extraction

RFFsNet-SEI:a multidimensional balanced-RFFs deep neural network framework for specific emitter identification

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Journal of Systems engineering and electronics 2024年第3期35卷 558-574,F0002页

作者： FAN Rong SI Chengke HAN Yi WAN Qun School of Information and Communication engineering University of Electronic Science and Technology of ChinaChengdu 611731China Institute of electronic and Electrical engineering Civil Aviation Flight University of ChinaGuanghan 618307China

Existing specific emitter identification(SEI)methods based on hand-crafted features have drawbacks of losing feature information and involving multiple processing stages,which reduce the identification accuracy of emitters and complicate the procedures of *** this paper,we propose a deep SEI approach via multidimensional feature extraction for radio frequency fingerprints(RFFs),namely,***,we extract multidimensional physical RFFs from the received signal by virtue of variational mode decomposition(VMD)and Hilbert transform(HT).The physical RFFs and I-Q data are formed into the balanced-RFFs,which are then used to train *** introducing model-aided RFFs into neural network,the hybrid-driven scheme including physical features and I-Q data is *** improves physical interpretability of ***,since RFFsNet-SEI identifies individual of emitters from received raw data in end-to-end,it accelerates SEI implementation and simplifies procedures of ***,as the temporal features and spectral features of the received signal are both extracted by RFFsNet-SEI,identification accuracy is ***,we compare RFFsNet-SEI with the counterparts in terms of identification accuracy,computational complexity,and prediction *** results illustrate that the proposed method outperforms the counterparts on the basis of simulation dataset and real dataset collected in the anechoic chamber.

关键词： specific emitter identification(SEI) deep learning(DL) radio frequency fingerprint(RFF) multidimensional feature extraction(MFE) variational mode decomposition(VMD)

An adaptive 3D reconstruction method for asymmetric dual-angle multispectral stereo imaging system on UAV platform

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Science China(Information Sciences) 2024年第8期67卷 285-299页

作者： Chen WANG Xian LI Yanfeng GU Zixu WANG School of electronics and Information engineering Harbin Institute of Technology Beijing Institute of Control and electronic Technology

A multispectral imaging system often cannot capture 3D spatial information owing to hardware limitations, which diminishes the effectiveness across various domains. To address this problem, we have developed a multispectral stereo imaging system along with an adaptive 3D reconstruction algorithm. Unlike existing unmanned aerial vehicle stereo imaging systems, our multispectral stereo imaging system uses two multispectral cameras with asymmetric spectral bands positioned at different angles. This design enables the acquisition of a higher number of bands and lateral spatial information while maintaining a lightweight structure. This system introduces challenges such as large geometric distortions and intensity differences between multiple bands. To accurately recover 3D spatial information, we propose an adaptive 3D reconstruction method. This method employs a position and orientation system-assisted projection transformation and a normalized threshold adjustment strategy. Finally, mutual information is used to reconstruct the multispectral images densely, effectively addressing nonlinear differences and generating a comprehensive multispectral point cloud. Our stereo system was used for two real data collections in different regions, and the efficacy of the proposed 3D reconstruction method was validated by comparing it with existing methods and commercial software.

关键词： 3D reconstruction feature extraction multispectral images stereo imaging system unmanned aerial vehicle

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

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China Communications 2024年第1期21卷 148-162页

作者： Yizhe Zhao Yanliang Wu Jie Hu Kun Yang School of Information and Communication engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower *** this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)*** joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless *** the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)*** results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

关键词： energy harvesting modulation(EHM) integrated data and energy transfer(IDET) performance analysis wireless data transfer(WDT) wireless energy transfer(WET)

The Combined Effect of Spin-Transfer Torque and Voltage-Controlled Strain Gradient on Magnetic Domain-Wall Dynamics:Toward Tunable Spintronic Neuron

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Chinese Physics Letters 2024年第5期41卷 120-137页

作者：郁国良何鑫岩施胜宾邱阳朱明敏王嘉维李燕李元勋王杰周浩淼 College of Information engineering China Jiliang UniversityHangzhou 310018China The Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province Hangzhou 310018China Department of engineering Mechanics Zhejiang UniversityHangzhou 310027China School of electronic Science and engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Magnetic domain wall(DW), as one of the promising information carriers in spintronic devices, have been widely investigated owing to its nonlinear dynamics and tunable properties. Here, we theoretically and numerically demonstrate the DW dynamics driven by the synergistic interaction between current-induced spin-transfer torque(STT) and voltage-controlled strain gradient(VCSG) in multiferroic heterostructures. Through electromechanical and micromagnetic simulations, we show that a desirable strain gradient can be created and it further modulates the equilibrium position and velocity of the current-driven DW motion. Meanwhile, an analytical Thiele's model is developed to describe the steady motion of DW and the analytical results are quite consistent with the simulation data. Finally, we find that this combination effect can be leveraged to design DW-based biological neurons where the synergistic interaction between STT and VCSG-driven DW motion as integrating and leaking motivates mimicking leaky-integrate-and-fire(LIF) and self-reset function. Importantly, the firing response of the LIF neuron can be efficiently modulated, facilitating the exploration of tunable activation function generators, which can further help improve the computational capability of the neuromorphic system.

关键词： tunable synergistic integrating

A Novel CCA-NMF Whitening Method for Practical Machine Learning Based Underwater Direction of Arrival Estimation

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Journal of Beijing Institute of Technology 2024年第2期33卷 163-174页

作者： Yun Wu Xinting Li Zhimin Cao School of Physics and electronic engineering Northeast Petroleum UniversityDaqing 163318China

Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical *** to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation *** order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian ***,the obtained information about non-Gaussian components can be used to whiten the array *** on these considerations,a novel practical sonar array whitening method was ***,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array *** the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation *** results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.

关键词： direction of arrival(DOA) sonar array data underwater disturbance machine learn-ing canonical correlation analysis(CCA) non-negative matrix factorization(NMF)

Attention Guided Food Recognition via Multi-Stage Local Feature Fusion

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Computers, Materials & Continua 2024年第8期80卷 1985-2003页

作者： Gonghui Deng Dunzhi Wu Weizhen Chen School of Electrical and electronic engineering Wuhan Polytechnic UniversityWuhan430048China

The task of food image recognition,a nuanced subset of fine-grained image recognition,grapples with substantial intra-class variation and minimal inter-class *** challenges are compounded by the irregular and multi-scale nature of food *** these complexities,our study introduces an advanced model that leverages multiple attention mechanisms and multi-stage local fusion,grounded in the ConvNeXt *** model employs hybrid attention(HA)mechanisms to pinpoint critical discriminative regions within images,substantially mitigating the influence of background ***,it introduces a multi-stage local fusion(MSLF)module,fostering long-distance dependencies between feature maps at varying *** approach facilitates the assimilation of complementary features across scales,significantly bolstering the model’s capacity for feature ***,we constructed a dataset named Roushi60,which consists of 60 different categories of common meat *** evaluation of the ETH Food-101,ChineseFoodNet,and Roushi60 datasets reveals that our model achieves recognition accuracies of 91.12%,82.86%,and 92.50%,*** figures not only mark an improvement of 1.04%,3.42%,and 1.36%over the foundational ConvNeXt network but also surpass the performance of most contemporary food image recognition *** advancements underscore the efficacy of our proposed model in navigating the intricate landscape of food image recognition,setting a new benchmark for the field.

关键词： Fine-grained image recognition food image recognition attention mechanism local feature fusion