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International Symposium on Computational Intelligence and Design, ISCID

作者： Kaixuan Chen Shuping He Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Hefei China

ISBN: (纸本)9781665438575

This work investigates the fault-tolerant control scheme for Takagi-Sugeno fuzzy semi-Markov jump systems with actuator faults. The hidden semi-Markov model is employed to describe the asynchronous phenomenon between the controller and plant. Based on Lyapunov theory, the fault tolerant controller depending on observable mode is presented to make sure that the semi-Markov jump systems is stochastically stable and satisfies the $H_{\infty}$ performance. A simulation example via a single-link robot is employed to prove the correctness of the studied approach.

关键词： Actuators Sufficient conditions Computational modeling Fault tolerant systems Fault tolerant control Manipulators Takagi-Sugeno model

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Robust DOA Estimation Based on Dual Lawson Norm for RIS-Aided Wireless Communication Systems

arXiv

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arXiv 2024年

作者： Yu, Canping Li, Yingsong Li, Liping Huang, Zhixiang Wu, Qingqing de Lamare, Rodrigo C. The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei230601 China The Department of Electronic Engineering Shanghai Jiao Tong University 200240 China Gávea 22451-900 Brazil The School of Physics Engineering and Technology University of York YorkYO10 5DD United Kingdom

Reconfigurable intelligent surfaces (RIS) can actively perform beamforming and have become a crucial enabler for wireless systems in the future. The direction-of-arrival (DOA) estimates of RIS received signals can help design the reflection control matrix and improve communication quality. In this paper, we design a RIS-assisted system and propose a robust Lawson norm-based multiple-signal-classification (LN-MUSIC) DOA estimation algorithm for impulsive noise environments, which is divided into two parts: first, the non-convex Lawson norm is used as the error criterion along with a regularization constraint to formulate the optimization problem. Then, a Bregman distance based alternating-direction-method-of-multipliers (ADMM) is used to solve the problem and recover the desired signal. The second part is to use the multiple-signal-classification (MUSIC) to find out the DOAs of targets based on their sparsity in the spatial domain. In addition, we also propose a RIS control matrix optimization strategy that requires no channel state information (CSI), which effectively enhances the desired signals and improves the performance of the LN-MUSIC algorithm. A Cramér–Rao-lower-bound (CRLB) of the proposed DOA estimation algorithm is presented and verifies its feasibility. Simulated results show that the proposed robust DOA estimate algorithm based on the Lawson norm can effectively suppress the impact of large outliers caused by impulsive noise on the estimation results, outperforming existing *** Codes - Copyright © 2024, The Authors. All rights reserved.

关键词： Impulse noise

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Hidden Attractors in a Delayed Memristive Differential System with Fractional Order and Chaos Synchronization

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Journal of Harbin Institute of Technology(New Series) 2020年第1期27卷 67-75页

作者： Dawei Ding Yecui Weng Nian Wang School of Electronics and Information Engineering Anhui UniversityHefei 230601China Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationAnhui UniversityHefei 230601China

As an important research branch,memristor has attracted a range of scholars to study the property of memristive chaotic ***,time⁃delayed systems are considered a significant and newly⁃developing field in modern *** combining memristor and time⁃delay,a delayed memristive differential system with fractional order is proposed in this paper,which can generate hidden ***,we discussed the dynamics of the proposed system where the parameter was set as the bifurcation parameter,and showed that with the increase of the parameter,the system generated rich chaotic phenomena such as bifurcation,chaos,and *** we derived adequate and appropriate stability criteria to guarantee the system to achieve ***,examples were provided to analyze and confirm the influence of parameter a,fractional order q,and time delayτon chaos *** simulation results confirm that the chaotic synchronization is affected by a,q andτ.

关键词： fractional order memristive time⁃delay hidden attractors chaos synchronization

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Surface Simulation and Design of C-band Energy Selective Surface

Surface Simulation and Design of C-band Energy Selective Sur...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Shangyu Lu Guohui Yang Kuang Zhang Yingsong Li School of Electronics and Information Engineering Harbin Institute of Technology Harbin China Anhui Province Key Laboratory of Target Recognition and Feature Extraction LuAn China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

Based on the equivalent circuit model of PIN diode and the full wave simulation method of CST software, the system performance of finite large energy selective surface (ESS) is simulated and analyzed when the number of cells is small. The simulation results show that the working performance of ESS will be degraded by the slight surface deformation caused by external force but not fail completely. Therefore, in the practical application of ESS, attention should be paid to avoid deformation caused by external force extrusion, which will reduce the shielding performance of ESS. The simulation results provide reference value for the practical design and application of energy selective surface.

关键词： Analytical models Deformation Surface waves PIN photodiodes Simulation System performance Force

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Understanding the Robustness of 3D Object Detection with Bird'View Representations in Autonomous Driving

Understanding the Robustness of 3D Object Detection with Bir...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zijian Zhu Yichi Zhang Hai Chen Yinpeng Dong Shu Zhao Wenbo Ding Jiachen Zhong Shibao Zheng Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Dept. of Comp. Sci. and Tech. THBI Lab Institute for AI Tsinghua University BNRist Center Zhongguancun Laboratory Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Computer Science and Technology Anhui University SAIC Motor AI Lab

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations; 2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features; 3) Camera-LiDARfusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models.

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Self-decoupling 5G MIMO Antenna via Grounding for Mobile Phones

Self-decoupling 5G MIMO Antenna via Grounding for Mobile Pho...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Wei Zhou Junwei Qi Yingsong Li College of Information and Communication Engineering Harbin Engineering University (HEU) China College of Computer Science and Technology HEU China Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University Hefei China

This paper presents a self-decoupling high isolation terminal antenna for mobile phones which can applied to 5G multiple-input-multiple-output (MIMO) communication systems. The significant decoupling effect is achieved by introducing only one ground point in each asymmetric antenna pair with an interval of very close (2mm). Through the simulations and optimizations, it can be obtained that the bandwidth of the two antennas is different owing-to the asymmetric structures of the constructed MIMO antenna. The -10 dB resonant frequency ranges of the two antennas are 4.65 - 5.17 GHz and 4.45 - 5.58 GHz, respectively, but the coincidence bandwidth of the two antennas covers the 5G band of 4.8 - 5 GHz, and the coupling of the proposed MIMO antenna in the same bandwidth is lower than -18dB as well.

关键词： Couplings Wireless communication 5G mobile communication Grounding Resonant frequency Bandwidth Mobile antennas

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RGBT Tracking via Progressive Fusion Transformer with Dynamically Guided Learning

arXiv

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arXiv 2023年

作者： Zhu, Yabin Li, Chenglong Wang, Xiao Tang, Jin Huang, Zhixiang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing of Anhui Higher Education Institutes School of Electronic and Information Engineering Anhui University Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China

Existing Transformer-based RGBT tracking methods either use cross-attention to fuse the two modalities, or use self-attention and cross-attention to model both modality-specific and modality-sharing information. However, the significant appearance gap between modalities limits the feature representation ability of certain modalities during the fusion process. To address this problem, we propose a novel Progressive Fusion Transformer called ProFormer, which progressively integrates single-modality information into the multimodal representation for robust RGBT tracking. In particular, ProFormer first uses a self-attention module to collaboratively extract the multimodal representation, and then uses two cross-attention modules to interact it with the features of the dual modalities respectively. In this way, the modality-specific information can well be activated in the multimodal representation. Finally, a feed-forward network is used to fuse two interacted multimodal representations for the further enhancement of the final multimodal representation. In addition, existing learning methods of RGBT trackers either fuse multimodal features into one for final classification, or exploit the relationship between unimodal branches and fused branch through a competitive learning strategy. However, they either ignore the learning of single-modality branches or result in one branch failing to be well optimized. To solve these problems, we propose a dynamically guided learning algorithm that adaptively uses well-performing branches to guide the learning of other branches, for enhancing the representation ability of each branch. Extensive experiments demonstrate that our proposed ProFormer sets a new state-of-the-art performance on RGBT210, RGBT234, LasHeR, and VTUAV datasets. In particular, the improvements of ProFormer on the LasHeR dataset are up to +6.2%/+ 4.1% in PR/SR compared with existing best RGBT tracker. Copyright © 2023, The Authors. All rights reserved.

关键词： Learning algorithms

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Electromagnetic Scattering from One-dimensional Gaussian Rough Surface Based on Stochastic Integral Equation

Electromagnetic Scattering from One-dimensional Gaussian Rou...

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International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO)

作者： An Qi Wang Meng Nan Zhu Zhi Xiang Huang Key Laboratory of intelligent Computing & Signal Processing Anhui University Hefei China Key Laboratory of intelligent Computing & Signal Processing Anhui University

ISBN: (数字)9781728169668

ISBN: (纸本)9781728169675

In this paper, the stochastic integral equation method (SIEM) is proposed to calculate the electromagnetic scattering from the one-dimensional Gaussian rough surface. In the SIEM, the statistical parameters of the Gaussian rough surface are firstly included in the Green's function. And the new Green's function is used to get the new integral equation. Then the method of moments is applied to solve the new integral equation. The accuracy of the SIEM is shown by comparing with the statistical average of multiple samples through the Monte Carlo method. And, the sample of the Gaussian rough surface is not needed to simulate in the SIEM.

关键词： Integral equations Electromagnetic scattering Stochastic processes Surface roughness Rough surfaces Numerical models Optimization

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Design of Miniaturized UWB Low Noise Amplifier Based on 65nm CMOS Technology

Design of Miniaturized UWB Low Noise Amplifier Based on 65nm...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Qing Guo Yuting Chen Xianliang Wu Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Institute of Physical Science and Information Technology Anhui University Hefei China

ISBN: (纸本)9781665409889

An X-band CMOS low noise amplifier (LNA) with flat gain and noise Figure (NF) is proposed in this paper. To achieve sufficient gain, the LNA adopts two-stage topology. A feed-back transformer is used at the input terminal to implement noise and wideband input matching. Transformer-based inter-stage and output matching networks are adopted to achieve well isolation and compact size. By introducing inductive peaking technique, the proposed LNA obtain lower NF and extend the bandwidth. Post simulation results show that the LNA achieves a gain of 14.6± 2dB and NF of 2. 5-3.3dB across a bandwidth from 8.5 GHz to 12.5 GHz. With the supply voltage of 1 V at the first stage and 1.8 V at the second stage, the dc power dissipation is 20.8 mW. The simulated input 1dB compression point ($\mathrm{P}_{\mathrm{l}\mathrm{d}\mathrm{B}}$) is -27.3dBm. The core chip area is only 0.41× 0.87mm 2 .

关键词： Low-noise amplifiers Impedance matching Simulation Voltage Transformer cores Transformers CMOS technology

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Multi-Granularity Prosodic Speech Synthesis with Grammar Information

SSRN

引用

SSRN 2024年

作者： Zhou, Jian Liu, Jiahui Fan, Cunhang Zheng, Wenming Lv, Zhao Tao, Liang Kwan, Hon Keung The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China Ministry of Education School of Biological Science and Medical Engineering Southeast University Nanjing210096 China The Department of Electrical and Computer Engineering University of Windsor WindsorN9B 3P4 Canada

Personalized speech synthesis involves learning an individual's unique speaking patterns from a reference audio to generate speech that mimics the speaker's habitual rhythm. However, the one-to-many mapping between text and speech, combined with the dynamic nature of personalized speech style characteristics in the reference audio, poses significant challenges for accurate personalized speech synthesis. In this paper, we propose a Grammar Infused Multi-granularity Prosody Network (GMG ProsodyNet) for personalized speech synthesis. Specifically, 1) We model prosodic features hierarchically at the levels of utterance, content syntax, word, and phoneme. We utilize the utterance-level prosodic feature to guide the prediction of fine-grained prosodic features according to the hierarchical property of prosodic features. We introduce a context syntax encoder to improve the prediction accuracy of duration, pitch, and energy characteristics in the synthesized audio. The proposed word-level prosodic encoder can efficiently extract valuable pitch dynamic and speech continuity features from the word spectrum. For controlling subtle prosodic nuances, we employ phoneme-level prosodic modeling. 2) We extract syntax level prosodic features from the syntax graph constructed by Graph Neural Network (GNN) with word as node, exploiting grammatical dependencies between distant words. Experimental results demonstrate that the proposed GMG ProsodyNet can effectively encode delicate and personalized prosodic features, leading to improved speech synthesis quality, fluency, and naturalness. © 2024, The Authors. All rights reserved.

关键词： Speech synthesis

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