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8th International Conference on Computer Science and Application engineering, CSAE 2024

作者： Liu, Shuyan Wang, Kangsheng School of Information Science and Engineering Yunnan University Yunnan Kunming China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9798400718090

In this article, we will review our advances in intelligence modeling the mind and explore various efforts to mimic the processes that would allow humans to perform cognition files and line widgets of processing. It presents ideas and stresses how understanding cognitive functions is vital for AI progress. Three principal modeling strategies are examined: cognitive mind modeling, assignation mind modeling, and intelligent body mind modeling. In the article, he explores a few theories, such as symbol systems and the ACT-R framework. It further argues that learning seems limited in encoding models of the mind, citing its successes in language-oriented tasks and its limitations in translating basic mechanisms like reward to model-level language and data from neuroscience. Additionally, it investigates ways of assessing and enhancing learning theory of mind abilities based on tasks that utilize end-to-end function. The review reiterates the need for an improved understanding of human-level thought processing to develop intelligent systems that can better discern intentions and feelings. It provides some ideas on evaluating this based on deep learning approaches. The review argues that viewing learning through the lens of systems yields new insights into human thought and social behavior that could enable the development of novel and more adaptive AI technologies. © 2024 Copyright held by the owner/author(s).

关键词： Contrastive Learning

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An Improved PID control Method Based on the Kalman Filter Algorithm 5

An Improved PID Control Method Based on the Kalman Filter Al...

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5th International Conference on Advances in Electrical engineering and Computer Applications, AEECA 2024

作者： Yan, Jihong Wang, Wentao Gou, Zhongyi Huang, Yizhan Ren, Mengxu Yan, Zhihao Wang, Xuechao Meng, Jianping Quzhou China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China

ISBN: (纸本)9798350355253

With the increasing demand for high-tech equipment, the need for reliable power supplies has grown, making the stability and accuracy of power supplies particularly critical. In the industrial sector, PID (Proportional-Integral-Derivative) control is the most commonly used method. However, white noise in the power supply and overshoot during system startup can cause instability in traditional PID controllers. To address this issue, this paper proposes a method to enhance the stability and accuracy of power supply output voltage by combining PID controllers with the Kalman filtering algorithm. The Kalman filter is used to process input errors by filtering. Based on the system's dynamic and measurement models, the Kalman filter provides an optimal estimate of the system state through predictions and updates of measurement data. Simulation results demonstrate that the Kalman filtering algorithm effectively reduces measurement errors and noise, mitigating output instability caused by process noise and significantly improving the performance and stability of the PID controller. © 2024 IEEE.

关键词： Three term control systems

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Intelligent Architecture for Multi-Domain Aerial-Surface-Underwater Networks with Hybrid Radio-Acoustic-Optical communications 10

Intelligent Architecture for Multi-Domain Aerial-Surface-Und...

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10th IEEE Smart World Congress, SWC 2024

作者： Zhang, Licheng Liu, Xingang Wu, Shaozhi University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Chengdu China

ISBN: (纸本)9798331520861

Multi-domain aerial-surface-underwater networks are increasingly critical in applications such as maritime surveillance and rescue. However, due to environmental and technical constraints, traditional communication methods alone are often insufficient, particularly in cross-domain and underwater-domain communication scenarios. Currently, there is very limited research on aerial-surface-underwater communication networks. To address the challenge of seamlessly integrating these diverse domains, this paper proposes an intelligent architecture that optimizes communication network across aerial, surface, and underwater domains with hybrid radio-acoustic-optical communications by leveraging the complementary strengths of different communication technologies. The proposed architecture comprises three layers, in intelligence layer, integrated resource management model, dynamic routing decision model and adaptive service-rate sensing model. To evaluate the performance, this paper conducts case studies in different hybrid multi-domain network scenarios through simulation and experiment. It can be concluded that the proposed intelligent architecture could effectively integrate hybrid radio-acoustic-optical communication technologies with complementary strengths and enhance efficiency and robustness of multi-domain aerial-surface-underwater communication network. This research provides an innovative framework for advancing the development of multi-domain networks with hybrid communication technologies. © 2024 IEEE.

关键词： Resource allocation

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A PID control Algorithm Optimized by PSO-BP Neural Network and Kalman Filter 5

A PID Control Algorithm Optimized by PSO-BP Neural Network a...

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5th International Conference on Advances in Electrical engineering and Computer Applications, AEECA 2024

作者： Yan, Jihong Gou, Zhongyi Wang, Wentao Yan, Zhihao Ren, Mengxu Huang, Yizhan Meng, Jianping Wang, Xuechao Quzhou China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China

ISBN: (纸本)9798350355253

In the power supply, stability and accuracy are important indicators. Unstable and inaccurate power supply could damage to the circuit and entire system. For the power supply system, the most common control method is PID control to resolve the issue but it cease to be effective in the nonlinear system and could be affected by noise easily. This paper introduces a PID control algorithm optimized by PSO-BP algorithm and Kalman filter, which introduces neural network to solve the problem that the performance of traditional PID algorithm may be reduced in nonlinear system. PID system parameters are adjusted by adaptive adjusting network weights. At the same time, this paper introduces PSO algorithm. By this way, the initial weight of the network could be optimized. Filtering the input signal by Kalman filter can effectively reduce the impact of noise. This optimized algorithm can effectively improve the unstable output caused by the system process noise and improve the output voltage of PID controller stability in nonlinear system. © 2024 IEEE.

关键词： Kalman filters

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Secret key rate of continuous-variable quantum key distribution with finite codeword length

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Science China(information Sciences) 2023年第8期66卷 150-151页

作者： Yan FENG Runhe QIU Kun ZHANG Xue-Qin JIANG Meixiang ZHANG Peng HUANG Guihua ZENG School of Information Science and Technology Donghua University School of Electronics and Information Soochow University School of Information Engineering Yangzhou University State Key Laboratory of Advanced Optical Communication Systems and Networks Center of Quantum Sensing and Information Processing (QSIP) Shanghai Jiao Tong University

In recent years, continuous-variable quantum key distribution(CV-QKD) has been proposed as a promising alternative to the most commonly implemented discrete-variable QKD [1]. A typical CV-QKD system includes mainly tw...

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Two efficient beamforming methods for hybrid IRS-aided AF relay wireless networks

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Science China(information Sciences) 2025年第4期68卷 363-379页

作者： Xuehui WANG Qingbo LI Wen ZHU Feng SHU Mengxing HUANG Fuhui ZHOU Riqing CHEN Cunhua PAN Yongpeng WU Jiangzhou WANG School of Mathematics and Statistics Hainan Normal University Key Laboratory of Data Science and Smart Education Ministry of Education Hainan Normal University School of Information and Communication Engineering Hainan University Collaborative Innovation Center of Information Technology Hainan University School of Electronic and Optical Engineering Nanjing University of Science and Technology College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Digital Fujian Institute of Big Data for Agriculture Fujian Agriculture and Forestry University National Mobile Communications Research Laboratory Southeast University Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University School of Engineering University of Kent

Owing to its ability to mitigate the double-fading effect by amplifying the reflected signal, the active intelligent reflecting surface(IRS) has garnered significant attention. In this paper, an amplify-and-forward(AF) relay network assisted by a hybrid IRS consisting of both passive and active units is developed. A signal-to-noise ratio(SNR) maximization problem is formulated, where the AF relay beamforming matrix and the hybrid IRS reflecting coefficient matrices for two-time slots need to be optimized. To address the SNR maximization problem, this paper proposes both a high-performance(HP) method and a low-complexity(LC) method. The HP method is based on the semidefinite relaxation and fractional programming(SDR-FP)algorithm, with rank-1 solutions obtained through Gaussian randomization. For the LC method, the amplification coefficient of each active IRS element is assumed to be equal. The SNR maximization problem is then addressed using the whitening filter,generalized power iteration, and generalized Rayleigh-Ritz(WF-GPI-GRR) approach. Simulation results show that compared with the benchmarks, such as the passive IRS-aided AF relay network, the proposed HP-SDR-FP and WF-GPI-GRR methods achieve significant rate improvements. In particular, the HP-SDR-FP and WF-GPI-GRR methods yield more than a 135.0%rate gain when the transmit power Ps of the source is 10 dBm. Furthermore, the proposed HP-SDR-FP method outperforms the WF-GPI-GRR method in terms of rate performance.

关键词： double-fading intelligent reflecting surface active elements passive elements hybrid IRS AF relay

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Modulation technology in Cross-Domain Magnetic Induction communication 14

Modulation Technology in Cross-Domain Magnetic Induction Com...

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14th IEEE International Conference on Signal Processing, communications and Computing, ICSPCC 2024

作者： Cheng, Ruoxue Zhang, Xin Qi, Xiaoming Zhang, Xiaoji Ge, Yizhou School of Marine Science and Technology Northwestern Polytechnical University Xi'an China Science and Technology on Communication Information Security Control Laboratory Jiangxi China

ISBN: (纸本)9798350366556

The research on technology of cross-domain communication, which spans air and sea domains, has been widely concerned. As an emerging cross-domain communication technology, magnetic induction (MI) communication boasts unique advantages such as stable channels, minimal susceptibility to the dynamic ocean environment, and low propagation delay. However, it also has limitations in terms of transmission distance×data rate. In this paper, the modulation technology in cross-domain magnetic induction communication is studied, and the very minimum shift keying (VMSK/2) coding modulation scheme based on direct sequence spread spectrum (DSSS) technology is proposed. VMSK modulation is used to adapt to the severely bandwidth-limited underwater magnetic induction channel, and DSSS technology is used to enhance the detection ability of weak magnetic induction signal, thereby increasing the water entry depth of cross-domain communication. In this paper, the scheme of VMSK/2-DSSS code modulation is given, and the simulation analysis and field trial are carried out. The simulation and lake test results show that compared to magnetic induction communication without DSSS, the VMSK/2-DSSS coding modulation scheme can achieve a greater water entry depth, enabling error-free cross-domain magnetic induction communication at a depth of 40 meters and a data rate of 100bps. © 2024 IEEE.

关键词： Signal modulation

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Event-Triggered Distributed Multi-sensor Data Fusion for Networked Systems with Delayed Measurements 5th

Event-Triggered Distributed Multi-sensor Data Fusion for Ne...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Zang, Zeyuan Zhu, Cui Wang, Zhangang Luo, Yuhao School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China

ISBN: (纸本)9789811939976

An event-triggered distributed data fusion algorithm is proposed for the multi-sensor systems suffering from delayed measurements due to the unreliability of network. A communication mechanism to determine whether to transmit measurement data according to specific conditions is introduced to reduce excessive transmissions. Then a novel distributed multi-sensor data fusion algorithm with buffers has been proposed. The performance of the system is analyzed and it shows that the error covariance after fusing is smaller and the performance of the fusion center is much better than that without buffer. A numerical example is given to demonstrate the effectiveness of the proposed algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sensor data fusion

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Efficient Real-Time Recognition Model of Plant Diseases for Low-Power Consumption Platform

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2040-2054页

作者： Deng, Songyun Wu, Wanneng Zou, Kunlin Qin, Hai Cheng, Lekai Liang, Qiaokang Hunan University College of Electrical and Information Engineering Changsha410082 China Changsha University of Science and Technology School of Electrical and Information Engineering Changsha410114 China Hunan University National Engineering Research Center for Robot Vision Perception and Control College of Electrical and Information Engineering Changsha410082 China

Recognition and early warning of plant diseases is one of the keys to agricultural disaster prevention and mitigation. Deep learning-based image recognition methods give us a new idea for plant disease identification. Due to the harsh conditions in agricultural environment, recent research has focused on exploring ways to lightweight the recognition model for deployment on low-power devices. In this article, we propose an efficient and feature-guided real-time plant disease recognition model with a multiclassifier architecture, specifically designed for low-power devices. By comparing with other advanced methods, our model reaches the state of the art in the combined metrics of recognition accuracy, the number of parameters, and inference speed. First, we propose AMI-NanoNet based on Roofline theory to significantly reduce the number of parameters and computational complexity. This model can achieve 99.8343% accuracy on PlantVillage by using a feature-guided curriculum learning with stepwise training strategy. Moreover, we design another training strategy suitable for lightweight ensemble models. Based on this strategy, our model only needs to integrate the classifiers at the end of the network to achieve 99.8708% identification accuracy, and it hardly increases the number of operations and parameters of the network. Extensive evaluations on this dataset demonstrate the effectiveness of our ensemble learning method. Furthermore, we tested our proposed methods on another dataset from other domains to validate its applicability to different scenarios. Overall, our research provides a basis for rapid and intelligent identification of plant diseases. © 2023 IEEE.

关键词： Real time systems

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Polarization-Space-Time Processing in Mainlobe Blanket Jamming via CP Decomposition 8

Polarization-Space-Time Processing in Mainlobe Blanket Jammi...

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8th International Conference on Signal and Image Processing, ICSIP 2023

作者： Pan, Bunian Wang, Bing Dong, Luxin Yao, Xue Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Science and Technology on Electronic Information Control Laboratory Chengdu610036 China Southeast University School of Information Science and Engineering Nanjing211100 China

ISBN: (纸本)9798350397932

This paper deals with the problem of mainlobe jamming suppression for phased-array radar system via a joint polarization-space-time processing method resorting to tensor decomposition. Firstly, a dual-polarization receiving array model is established. Then, base on the polarization-space-time characteristics, CANDECOMP/PARAFAC (CP) decomposition is leveraged to recast the received signals as a third-order tensor consisting of three factor matrices. Further, the target echo and the jamming signal can be obtained via minimizing the Frobenius norm of the approximation error between the factor matrices and their iteration forms. Finally, the effectiveness of the proposed method by numerical simulation is verified, showing its capability to resist mainlobe jamming compared with the art competing method. © 2023 IEEE.

关键词： Numerical methods

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