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Immune particle swarm optimization of linear frequency modulation in acoustic communication

Journal of Systems Engineering and Electronics 2015年第3期26卷 450-456页

作者： Haipeng Ren Yang Zhao Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

With the exploration of the ocean, underwater acoustic communication has attracted more and more attention in recent years. The underwater acoustic channel is considered to be one of the most complicated channels because it suffers from more serious multipath effect, fewer available bandwidths and quite complex noise. Since the signals experience a serious distortion after being transmitted through the underwater acoustic channel, the underwater acoustic communication experiences a high bit error rate （BER）. To solve this problem, carrier waveform inter- displacement （CWlD） modulation is proposed. It has been proved that CWlD modulation is an effective method to decrease BER. The linear frequency modulation （LFM） carrier-waves are used in CWlD modulation. The performance of the communication using CWID modulation is sensitive to the change of the frequency band of LFM carrier-waves. The immune particle swarm optimization （IPSO） is introduced to search for the optimal frequency band of the LFM carrier-waves, due to its excellent performance in solving complicated optimization problems. The multi-objective and multi- peak optimization nature of the IPSO gives a suitable description of the relationship between the upper band and the lower band of the LFM carrier-waves. Simulations verify the improved perfor- mance and effectiveness of the optimization method.

关键词： underwater acoustic communication carrier waveform inter-displacement (CWlD) multi-objective optimization immune particle swarm optimization (IPSO).

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Reversible spiking neural P systems

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Frontiers of Computer Science 2013年第3期7卷 350-358页

作者： Tao SONG Xiaolong SHI Jinbang XU Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Spiking neural （SN） P systems are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes. In this work, we investigate reversibility in SN P systems, as well as the computing power of reversible SN P systems. Reversible SN P systems are proved to have Turing creativity, that is, they can compute any recursively enumerable set of non-negative integers by simulating universal reversible register machine.

关键词： membrane computing spiking neural P system reversible computing model universality reversible register machine

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Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems

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Chinese Physics Letters 2010年第1期27卷 37-40页

作者：尚荣华焦李成李阳阳吴建设 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Institute of Intelligent Information Processing Xidian University Xi'an 710071

Based on the concept and principles of quantum computing and the principle of the immune clonal selection, a new algorithm for multi-objective 0/1 knapsack problems is introduced. In the algorithm, for the novel representation, qubit antibodies in the antibody population are updated by applying a new chaos update strategy. A quantitative metric is used for testing the convergence to the Pareto-optimal front. Simulation results on the 0/1 knapsack problems show that the new algorithm, in most cases, is more effective.

关键词： Chinese climate network complex systems small world community

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A Game Theory-Reinforcement Learning Approach to Cooperation for UAVs

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IEEE Transactions on Vehicular Technology 2025年

作者： Tang, Changbing Pan, Linchao Chen, Jie Liu, Yang Lai, Jingang The College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua321004 China The School of Mathematical Sciences Zhejiang Normal University Jinhua321004 China The Hangzhou School of Automation Zhejiang Normal University Hangzhou311231 China The College of Electronic Engineering National University of Defense Technology Hefei230037 China The School of Artificial Intelligence and Automation the Key Laboratory of Image Processing and Intelligent Control Education Ministry of China China Huazhong University of Science and Technology Wuhan430074 China

To execute a variety of collaborative tasks, the cooperation for unmanned aerial vehicles (UAVs) with complicated interactions under dynamic environments is a challenging and critical issue. This paper studies the cooperation issue for UAVs under dynamic environments through an approach of game theory-reinforcement learning (GT-RL) approach, which combines the advantages of both game theory and reinforcement learning. First, to cope with the complicated interactions of UAVs, the cluster of UAVs is modeled as a public goods game with asymmetrical environmental feedback. Then, reinforcement learning is adopted to optimize decision-making of UAVs under unknown and dynamic environments through comparing the dynamic behaviors of UAVs, where a novel dynamics system offers a more comprehensive understanding on cooperative behavior among UAVs. Finally, the simulation results show that the GT-RL approach can effectively promote cooperation among UAVs in completing the collaborative tasks. © 1967-2012 IEEE.

关键词： Adversarial machine learning

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Brightness temperature emitted by radiometer calibration load at millimeter wave band

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INTERNATIONAL JOURNAL OF INFRARED AND MILLIMETER WAVES 2001年第4期22卷 553-569页

作者： Xiao, ZH Zhang, ZY Guo, W Key Laboratory of Education Ministry of People's Republic of China for Image Processing and Intelligent Control China

In this paper, the DVRT(vector radiative transfer theory of densely distributed random discrete scatters) model to calculate the brightness temperature emitted by radiometer calibration load is presented. It takes the multiple scattering of isolation layer into account, which is neglected by the incoherent homogeneous model often used in calibration. Hence, it works much better than incoherent homogeneous model at millimeter wave band. Furthermore, the iteration of DVRT model is presented, and it proves that the incoherent homogeneous model is just the zero-order solution of DVRT model. Some numerical results are provided in the end.

关键词： DVRT model incoherent homogeneous model radiometer calibration calibration load brightness temperature

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An immune memory clonal algorithm for numerical and combinatorial optimization

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中国计算机科学前沿 2010年第4期4卷 536-559页

作者： Ruochen LIU Licheng JIAO Yangyang LI Jing LIU Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information ProcessingXidian UniversityXi'an 710071China

Inspired by the clonal selection theory together with the immune network model, we present a new artificial immune algorithm named the immune memory clonai algorithm (IMCA). The clonal operator,inspired by the immune system, is discussed first. The IMCA includes two versions based on different immune memory mechanisms; they are the adaptive immune memory clonal algorithm (AIMCA) and the immune memory clonal strategy (IMCS). In the AIMCA, the mutation rate and memory unit size of each antibody is adjusted dynamically. The IMCS realizes the evolution of both the antibody population and the memory unit at the same time. By using the clonal selection operator, global searching is effectively combined with local *** to the antibody-antibody (Ab-Ab) affinity and the antibody-antigen (Ab-Ag) affinity, The IMCA can adaptively allocate the scale of the memory units and the antibody population. In the experiments, 18 multimodal functions ranging in dimensionality from two, to one thousand and combinatorial optimization problems such as the traveling salesman and knapsack problems (KPs)are used to validate the performance of the IMCA. The computational cost per iteration is presented. Experimental results show that the IMCA has a high convergence speed and a strong ability in enhancing the diversity of the population and avoiding premature convergence to some degree. Theoretical roof is provided that the IMCA is convergent with probability 1.

关键词： artificial immune system (AIS) clonal selection immune memory immune network model evolutionary computation knapsack problem(KP) traveling salesman problem(TSP)

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A survey of distributed algorithms for aggregative games

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IEEE/CAA Journal of Automatica Sinica 2025年

作者： Li, Huaqing Li, Jun Ran, Liang Zheng, Lifeng Huang, Tingwen Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing The College of Electronic and Information Engineering Southwest University Chongqing400715 China College of Computer Science and Engineering Chongqing University of Technology Chongqing400054 China School of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen518107 China

Game theory-based models and design tools have gained substantial prominence for controlling and optimizing behavior within distributed engineering systems due to the inherent distribution of decisions among individuals. In non-cooperative settings, aggregative games serve as a mathematical framework model for the interdependent optimal decision-making problem among a group of non-cooperative players. In such scenarios, each player's decision is influenced by an aggregation of all players' decisions. Nash equilibrium (NE) seeking in aggregative games has emerged as a vibrant topic driven by applications that harness the aggregation property. This paper presents a comprehensive overview of the current research on aggregative games with a focus on communication topology. A systematic classification is conducted on distributed algorithm research based on communication topologies such as undirected networks, directed networks, and time-varying networks. Furthermore, it sorts out the challenges and compares the algorithms' convergence performance. It also delves into real-world applications of distributed optimization techniques grounded in aggregative games. Finally, it proposes several challenges that can guide future research directions. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Nash equilibrium

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Micro-assembly of micro parts using uncalibrated microscopes visual servoing method

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information Technology Journal 2008年第3期7卷 497-503页

作者： Xiangjin, Zeng Xinhan, Huang Min, Wang Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering HUST Wuhan 430074 China

In micromanipulation, the microscope vision servoing can achieve a high performance. In order to avoid the complicated calibration of intrinsic parameter of camera, We apply an improved broyden's method to estimate the image jacobian matrix on line, which employs Chebyshev polynomial to construct a cost function to approximate the optimization value, obtaining a fast convergence for online estimation. Using the estimated jacobian matrix, a PD visual controller is used to make features converge to desired values with satisfactory dynamic performance. The experiments of micro-assembly of micro parts m microscopes confirm that the proposed method is effective and feasible. © 2008 Asian Network for Scientific information.

关键词： Chebyshev polynomials

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Dual-mode predictive control of a rotor suspension system

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Science China(information Sciences) 2020年第1期63卷 178-189页

作者： Yue WU Gui-Ping REN Hai-Tao ZHANG Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and Technology State Key Laboratory of Digital Manufacturing Equipments and Technology

Rotor active magnetic bearing(rotor-AMB) systems are frequently used to alleviate vibrations for various applications such as in national defense, manufacturing industries, IC production, and aerospace engineering. One obstacle to improve machining efficiency and quality is the open-loop instability of rotorAMB systems during the machining process. We built a closed-loop processing platform using a spindle rotor installed with AMBs and thereby developed a rotor-AMB suspension system embedded with a dual-mode predictive controller(DMPC). The performance of the system is thus substantially improved. In the proposed DMPC, both model-based prediction and receding horizon optimization are utilized to guarantee the closedloop stability of the rotor-AMB suspension systems with input constraints. Finally, the effectiveness and superiority of the proposed method are examined through substantial levitation experiments on a machining platform with installed AMBs.

关键词： dual-mode predictive control system identification optimization control model predictive control suspension control

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Multi-objective carrier chaotic evolutionary algorithm for DNA sequences design

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Progress in Natural Science:Materials International 2007年第12期17卷 1515-1520页

作者： Xiao Jianhua, Xu Jin, Geng Xiutang and Pan Linqiang(key laboratory of image processing and intelligent control, Department of control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China) Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

DNA computing is a new vista of computation, which is of biochemical type. Since each piece of information is encoded in biological sequences, their design is crucial for successful DNA computation. DNA sequence design is involved with a number of design criteria, which is difficult to be solved by the traditional optimization methods. In this paper, the multi-objective carrier chaotic evolution algorithm (MCCEA) is introduced to solve the DNA sequence design problem. By merging the chaotic search base on power function carrier, a set of good DNA sequences are generated. Furthermore, the simulation results show the efficiency of our method.

关键词： DNA computing carrier chaotic search multi-objective evolutionary algorithm DNA sequences design.

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