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Hardware-friendly rate estimation algorithm and architecture design for AVS3

Multimedia Tools and Applications 2025年 1-19页

作者： Yan, Yunyao Xiang, Guoqing Chen, Jie Huang, Xiaofeng Zhang, Peng Jia, Huizhu Xie, Xiaodong School of Electronic and Computer Engineering Peking University Shenzhen China School of Computer Science Peking University Beijing China Advanced Institute of Information Technology Peking University Hangzhou China School of Communication Engineering Hangzhou Dianzi University Hangzhou China

To enhance the capabilities of advanced video coding for emerging applications, the AVS3 standard has been introduced to double the coding efficiency compared to its predecessor, the AVS2 standard. It incorporates sophisticated coding tools, such as advanced rate-distortion optimization (RDO), to select the optimal coding mode. The AVS3 standard further refines bit rate compression through Advanced Entropy Coding (AEC) within the RDO process. However, AEC demands significant computational resources due to its high data dependency and involves complex steps like binarization, context modeling, interval subdivision, renormalization, handling of outstanding bits, and context updating. Notably, the time complexity of AEC is predominantly due to context updating and interval subdivision, which are recursive and thus pose challenges for real-time applications, particularly in hardware implementations. Addressing these challenges, this paper introduces an adaptive rate estimation algorithm using a hardware-friendly piece-wise linear function to expedite bit rate calculations for AVS3 applications. Initially, we develop a linear rate estimation method based on the statistics of bin numbers. To preserve high coding performance, we further propose an adaptive model parameter updating method that adjusts weights dynamically based on varying video content. Building on this fast rate estimation algorithm, we propose a high-throughput hardware architecture that incorporates pipelining and parallelization to meet the stringent real-time requirements for 4K@120fps ultra-high-definition video at 200 MHz, with only a minimal increase in BD-rate by 1.06% under the All-Intra (AI) configuration. To our knowledge, this is the pioneering study focusing on hardware-oriented rate estimation for the AVS3 standard, marking a significant advancement in the field of video coding technology. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature

关键词： Video signal processing

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Turbulent drag reduction by sector-shaped counter-flow dielectric barrier discharge plasma actuator

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Chinese Physics B 2025年第2期34卷 362-370页

作者： Borui Zheng Shaojie Qi Minghao Yu Jianbo Zhang Linwu Wang Dongliang Bian School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048China Shaanxi University Key Laboratory of Photonic Power Devices and Discharge Regulation Xi’an 710048China

The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.

关键词： plasma flow control turbulent boundary layer turbulent drag reduction

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Extraction of Complex Sentence Relationships Based on Formalized Chinese Clause Structures 7

Extraction of Complex Sentence Relationships Based on Formal...

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7th International Conference on Machine Learning and Natural Language Processing, MLNLP 2024

作者： Hao, Wen School of Information and Control Engineering Xi'an University of Architecture Technology Xi'an710055 China

ISBN: (纸本)9798350354973

In the field of relation extraction (RE) from text, English clause structures have recently emerged as a promising method with significant practical value. However, applying this approach to Chinese clauses presents challenges due to the absence of formal structural representation. Our research shows that Chinese clauses follow a conditional probability function of the core relation P, which can be expressed as C = (S|P, O|P, SO|P), demonstrating a formal structural characteristic of discrete complementary synthesis. Notably, the O|P structure, with a high conditional probability, accounts for 79% of cases, serving as the core of complex sentence relations in Chinese. This sharply contrasts with the structural features of English clauses. Building on this, we propose the Discrete Complementary Synthesis Formal Structure (DCSFS) clause unit model. This model is employed to analyze and verify the role of the clause unit as the fundamental encoding element in Chinese sentences. Accordingly, we develop a method for automatically extracting semantic relations from complex Chinese sentences using this formalized clause unit model. Experimental results show that our approach outperforms existing punctuation-based clause determination methods and effectively addresses the challenges of extracting complex sentence relations from Chinese texts. © 2024 IEEE.

关键词： Semantics

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Dual-Path Dilated Convolutional Recurrent Network with Group Attention for Multi-Channel Speech Enhancement 48

Dual-Path Dilated Convolutional Recurrent Network with Group...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Cheng, Jiaming Pang, Cong Liang, Ruiyu Fan, Jingjie Zhao, Li Southeast University School of Information Science and Engineering China Nanjing Institute of Technology School of Information and Communication Engineering China

ISBN: (纸本)9781728163277

This paper proposes a dual-path convolutional recurrent network with group attention for ICASSP Signal Processing Grand Challenge: L3DAS23 Challenge. We design a structure based on convolutional encoder-decoder, and frequency-time blocks based on group attention are introduced in the middle. The encoder is used to extract the local representation from the complex spectrum, the correlation along the frequency axis and the time axis are captured through groups of time-frequency processing modules and the key information in the feature flow is extracted by the group attention. As a result, our system ranks the 1st place of the 3D speech enhancement task in L3DAS23 Challenge, and significantly outperforms the baseline, while achieving 0.101 WER and 0.902 STOI on the blind test-set. © 2023 IEEE.

关键词： deep learning frequency-time block group attention multi-channel speech enhancement speech enhancement

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An artificial systems,computational experiments and parallel execution-based surface electromyogram-driven anti-disturbance zeroing neurodynamic strategy for upper limb human-robot interaction control

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CAAI Transactions on Intelligence technology 2024年第2期9卷 511-525页

作者： Yongbai Liu Keping Liu Gang Wang Jiliang Zhang Yao Chou Zhongbo Sun Department of Mechanical Engineering Changchun University of TechnologyChangchunChina Department of Control Engineering Changchun University of TechnologyChangchunChina School of Electrical and Information Engineering Jilin Engineering Normal UniversityChangchunChina College of Information Science and Engineering Northeastern UniversityShenyangChina Department of Electrical and Computer Engineering Brigham Young UniversityProvoUtahUSA

In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ***,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be *** deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI *** upper limb-robotic exoskeleton system is re-modelled as an artificial *** on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical ***,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and *** results substantiate the global convergence and robustness of the proposed controller in the presence of different external *** addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.

关键词： neural network pattern recognition robotics signal processing

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An Energy Management System with Mobile Energy Station Based Wireless Energy Transfer:System Design and Prototype Implementation

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China communications 2025年第1期22卷 89-101页

作者： Yan Kang Li Jinhui Fan Xinyu Hu Jie Yu Qin Yang Kun Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001China School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

In indoor environments,various batterypowered Internet of Things(IoT)devices,such as remote controllers and electronic tags on high-level shelves,require efficient energy ***,manually monitoring remaining energy levels and battery replacement is both inadequate and *** paper introduces an energy management system for indoor IoT,which includes a mobile energy station(ES)for enabling on-demand wireless energy transfer(WET)in radio frequency(RF),some energy receivers(ERs),and a cloud *** implementing a two-stage positioning system and embedding energy receivers into traditional IoT devices,we robustly manage their energy *** experimental results demonstrate that the energy receiver can harvest a minimum power of 58 mW.

关键词： angle of arrival(AOA) Internet of Things(IoT) mobile station prototype wireless energy transfer(WET)

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Fault diagnosis method of link control system for gravitational wave detection

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Journal of Systems engineering and Electronics 2024年第4期35卷 922-931页

作者： GAO Ai XU Shengnan ZHAO Zichen SHANG Haibin XU Rui School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Ministry of Industry and Information TechnologyBeijing 100081China Key Laboratory of Dynamics and Control of Flight Vehicle Ministry of EducationBeijing 100081China

To maintain the stability of the inter-satellite link for gravitational wave detection,an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is *** from the traditional fault diagnosis optimization algorithms,the fault intelligent learning method pro-posed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong cou-pling *** constructing a two-layer learning network,the method enables efficient joint diagnosis of fault areas and fault *** simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s,and the fault diagnosis efficiency is improved by 99.8%compared with the traditional algorithm.

关键词： large scale multi-satellite formation gravitational wave detection laser link monitoring fault diagnosis deep learning

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Neuroadaptive Fault-Tolerant control for Uncertain Nonlinear Systems with New Time-Varying Constraints on States 7

Neuroadaptive Fault-Tolerant Control for Uncertain Nonlinear...

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7th International Symposium on Autonomous Systems, ISAS 2024

作者： Zhou, Shuyan Liu, Junjie Wang, Xuesong China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China

ISBN: (纸本)9798350363173

In this article, a neuroadaptive fault-tolerant control scheme is proposed for a class of nonlinear systems with actuator failures, full state constraints and unknown time-varying disturbances. Besides the constraint boundary is different from the common research which is connected with time, partial states and desired trajectory. Additionally, we employ neural networks to approximate the unknown nonlinear functions, and the problem of "explosion of complexity"is avoided by utilizing the dynamic surface control technique during the design process of conventional backstepping control. The control scheme can guarantee the ultimate bounded stable tracking and the full state constraints are not violated. Both the theoretical analysis and numerical simulation are presented to demonstrate the feasibility and effectiveness of the proposed method. © 2024 IEEE.

关键词： Numerical methods

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A deep decentralized privacy-preservation framework for online social networks

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Blockchain(Research and Applications) 2024年第4期5卷 163-174页

作者： Samuel Akwasi Frimpong Mu Han Emmanuel Kwame Effah Joseph Kwame Adjei Isaac Hanson Percy Brown School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang212013China Department of Computer Engineering Ghana Communication Technology UniversityAccraPMB 100Ghana Department of Electrical&Electronic Engineering Ghana Communication Technology UniversityAccraPMB 100Ghana Department of Computer Science and Information Systems Ashesi UniversityAccra3042Ghana Department of Telecommunication Engineering Ghana Communication Technology UniversityAccraPMB 100Ghana

This paper addresses the critical challenge of privacy in Online Social Networks(OSNs),where centralized designs compromise user *** propose a novel privacy-preservation framework that integrates blockchain technology with deep learning to overcome these *** methodology employs a two-tier architecture:the first tier uses an elitism-enhanced Particle Swarm Optimization and Gravitational Search Algorithm(ePSOGSA)for optimizing feature selection,while the second tier employs an enhanced Non-symmetric Deep Autoencoder(e-NDAE)for anomaly ***,a blockchain network secures users’data via smart contracts,ensuring robust data *** tested on the NSL-KDD dataset,our framework achieves 98.79%accuracy,a 10%false alarm rate,and a 98.99%detection rate,surpassing existing *** integration of blockchain and deep learning not only enhances privacy protection in OSNs but also offers a scalable model for other applications requiring robust security measures.

关键词： Preprocessing Privacy-preservation Blockchain Deep learning Online social network

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Multispectral radiation thermometry approach based on feasible region constraints-divide and conquer optimization

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Optics Express 2025年第10期33卷 20736-20753页

作者： Huang, Hairui Zhang, Wei Yu, Peifeng Xu, Jiawen Liu, Xin Gao, Shan Wang, Chao Zhang, Zezhan Niu, Yi Jiang, Jing Clean Energy Materials and Engineering Center School of Electronic Science and Engineering State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China Chengdu611731 China The State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision Instrument Tsinghua University Beijing100084 China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology School of Information and Communication Engineering Harbin Engineering University Harbin150001 China

Multispectral radiation thermometry is a widely used non-contact temperature measurement method, particularly in extreme environments. However, accurately retrieving the true temperature remains challenging due to the unknown emissivity of the object. This paper proposes a collaborative optimization approach (feasible region constraints-divide and conquer optimization), which combines a feasible domain constraints method (PCR-PSO) with a divide and conquer optimization algorithm (multi-BFGS). Simulation results show that the proposed approach reduces the temperature inversion error from 0.59% to 0.19% compared to the traditional BFGS algorithm. Experimental results obtained with stainless steel samples indicate an average error of less than 0.2% and an average processing time of 0.2 seconds, highlighting the potential for real-time temperature measurement in engineering applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Temperature measurement

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