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Uniform Solution to QSAT by P Systems with Proteins

电子学报(英文版) 2012年第4期21卷 667-672页

作者： LU Chun SHI Xiaolong Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

P systems are distributed parallel computing models in the area of membrane computing, which are inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. P systems with proteins on membranes are a class of P systems, which have proved to be very efficient computing devices. Specifically, it was known that the Quantified satisfiability problem (QSAT) of a Boolean formula can be solved by a semi-uniform family of P systems with proteins on membranes and with membrane division. However, it remains open whether a uniform families of P systems with proteins on membranes can solve in polynomial time exactly the class of problems PSPACE. In this work, we present a uniform solution to QSAT problem by P systems with proteins on membranes in a linear time with respect to both the number n of Boolean variables and the number m of clauses of the instance, which answers the above open problem.

关键词：蛋白质膜 P系统分布式并行计算多项式时间 PSPACE 高级结构细胞膜计算模型 Membrane computing, Membrane protein, PSPACE-complete problem, Quantified satisflability problem （QSAT problem）, Uniform solution.

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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 1. 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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Deep transfer learning-based decoder calibration for intracortical brain-machine interfaces

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Computers in Biology and Medicine 2025年第Pt A期192卷 110231-110231页

作者： Li, Xiao Dong, Xianxin Wang, Jun Mao, Haodong Tu, Xikai Li, Wei He, Jiping Li, Qiang Zhang, Peng Hubei Key Laboratory of Modern Manufacturing Quantity Engineering School of Mechanical Engineering Hubei University of Technology Wuhan430068 China Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Hubei Wuhan China MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical Engineering School of Engineering Sciences Huazhong University of Science and Technology Hubei Wuhan China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan China Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Intracortical brain-machine interfaces (iBMIs) aim to establish a communication path between the brain and external devices. However, in the daily use of iBMIs, the non-stationarity of recorded neural signals necessitates frequent recalibration of the iBMI decoder to maintain decoding performance, which requires collecting and labeling a large amount of new data. To address this challenge and minimize the time needed for decoder recalibration, we proposed an active learning domain adversarial neural network (AL-DANN). This model leveraged a substantial volume of historical data alongside a small amount of current data (four samples per category) to calibrate the decoder. By incorporating domain adversarial and active learning strategies, the model effectively transferred knowledge from historical data to new data, reducing the demand for new samples. We validated the proposed method using neural signals recorded from three monkeys performing different movements in a classification task or a regression task. The results showed that the AL-DANN outperformed existing state-of-the-art methods. Impressively, it required only four new samples per category for decoder recalibration, leading to a recalibration time reduction of over 80 %. To our knowledge, this is the first study to incorporate deep transfer learning into iBMI decoder calibration, highlighting the significant potential of applying deep learning technologies in iBMIs. © 2025

关键词： Adversarial machine learning

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Neural-Network-Based Nonlinear Model Predictive Tracking control of a Pneumatic Muscle Actuator-Driven Exoskeleton

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IEEE/CAA Journal of Automatica Sinica 2020年第6期7卷 1478-1488页

作者： Yu Cao Jian Huang IEEE Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

Pneumatic muscle actuators(PMAs)are compliant and suitable for robotic devices that have been shown to be effective in assisting patients with neurologic injuries,such as strokes,spinal cord injuries,etc.,to accomplish rehabilitation ***,because PMAs have nonlinearities,hysteresis,and uncertainties,etc.,complex mechanisms are rarely involved in the study of PMA-driven robotic *** this paper,we use nonlinear model predictive control(NMPC)and an extension of the echo state network called an echo state Gaussian process(ESGP)to design a tracking controller for a PMA-driven lower limb *** dynamics of the system include the PMA actuation and mechanism of the leg orthoses;thus,the system is represented by two nonlinear uncertain *** facilitate the design of the controller,joint angles of leg orthoses are forecasted based on the universal approximation ability of the ESGP.A gradient descent algorithm is employed to solve the optimization problem and generate the control *** stability of the closed-loop system is guaranteed when the ESGP is capable of approximating system *** and experiments are conducted to verify the approximation ability of the ESGP and achieve gait pattern training with four healthy subjects.

关键词： Echo state Gaussian process model predictive control neural network pneumatic muscle actuators-driven exoskeleton

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Switching mechanism for TiO_2 memristor and quantitative analysis of exponential model parameters

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Chinese Physics B 2015年第8期24卷 598-604页

作者：王小平陈敏沈轶 School of Automation Huazhong University of Science and Technology Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology

The memristor, as the fourth basic circuit element, has drawn worldwide attention since its physical implementation was released by HP labs in 2008. However, at the nano-scale, there are many difficulties for memristor physical realization. So a better understanding and analysis of a good model will help us to study the characteristics of a memristor. In this paper, we analyze a possible mechanism for the switching behavior of a memristor with a Pt/TiO2/Pt structure, and explain the changes of electronic barrier at the interface of Pt/TiO2. Then, a quantitative analysis about each parameter in the exponential model of memristor is conducted based on the calculation results. The analysis results are validated by simulation results. The efforts made in this paper will provide researchers with theoretical guidance on choosing appropriate values for(α, β, χ, γ) in this exponential model.

关键词： memristor switching behavior electronic barrier exponential model

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RLSESN-based PID adaptive control for a novel wearable rehabilitation robotic hand driven by PM-TS actuators

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International Journal of intelligent Computing and Cybernetics 2012年第1期5卷 91-110页

作者： Jun Wu Jian Huang Yongji Wang Kexin Xing Key Laboratory of Image Processing and Intelligent Control Department of Control Science and EngineeringHuazhong University of Science and TechnologyWuhanChina

Purpose-The purpose of this paper is to develop a novel wearable rehabilitation robotic hand driven by Pneumatic Muscle-Torsion Spring(PM-TS)for finger *** has complex nonlinear dynamics,which makes PM modelling *** realize high-accurate tracking for the robotic hand,an Echo State Network(ESN)-based PID adaptive controller is proposed,even though the plant model is ***/methodology/approach-To drive a single joint of rehabilitation robotic hand,the paper proposes a new PM-TS actuator comprising a Pneumatic Muscle(PM)and a Torsion Spring(TS).Based on the novel actuator,a wearable robotic hand is *** employing the model-free approximation capability of ESN,the RLSESN based PID adaptive controller is presented for improving the trajectory tracking performance of the rehabilitation robotic *** ESN together with Recursive Least Square(RLS)is called a RLSESN,where the ESN output weight matrix is updated by the online RLS learning ***–Practical experiments demonstrate the validity of the PM-TS actuator and indicate that the performance of the RLSESN based PID adaptive controller is better than that of the conventional PID *** addition,they also verify the effectiveness of the proposed rehabilitation robotic ***/value–A new PM-TS actuator configuration that uses a PM and a torsion spring for bi-directional movement of joint is *** utilizing the new PM-TS actuator,a novel wearable rehabilitation robotic hand for finger therapy is *** on the unknown plant model,the RLSESN_PID controller is proposed to attain satisfactory performance.

关键词： Robotics control systems controllers Actuators Adaptive system theory Wearable rehabilitation robotic hand Echo state network Pneumatic muscle Trajectory tracking

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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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A membrane-inspired algorithm with a memory mechanism for knapsack problems

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Journal of Zhejiang University-Science C(Computers and Electronics) 2013年第8期14卷 612-622页

作者： Juan-juan HE Jian-hua XIAO Xiao-long SHI Tao SONG Key Laboratory of Image Processing and Intelligent Control School of AutomationHuazhong University of Science and Technology The Logistics Research Center Nankai University

Membrane algorithms are a class of distributed and parallel algorithms inspired by the structure and behavior of living cells. Many attractive features of living cells have already been abstracted as operators to improve the performance of algorithms. In this work, inspired by the function of biological neuron cells storing information, we consider a memory mechanism by introducing memory modules into a membrane algorithm. The framework of the algorithm consists of two kinds of modules (computation modules and memory modules), both of which are arranged in a ring neighborhood topology. They can store and process information, and exchange information with each other. We test our method on a knapsack problem to demonstrate its feasibility and effectiveness. During the process of approaching the optimum solution, feasible solutions are evolved by rewriting rules in each module, and the information transfers according to directions defined by communication rules. Simulation results showed that the performance of membrane algorithms with memory cells is superior to that of algorithms without memory cells for solving a knapsack problem. Furthermore, the memory mechanism can prevent premature convergence and increase the possibility of finding a global solution.

关键词： Membrane algorithm Memory mechanism Knapsack problem

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Research advances and prospect of spiking neural P systems

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Jisuanji Xuebao/Chinese Journal of Computers 2008年第12期31卷 2090-2096页

作者： Pan, Lin-Qiang Zhang, Xing-Yi Zeng, Xiang-Xiang Wang, Jun 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 P systems are a new computing model inspired from the biological phenomena that in the brain the neurons cooperate to deal with spikes by axons. Since it has been shown that they have powerful computational capability and potential capability in solving computationally hard problems, more and more people begin to get interested in this field. This paper firstly introduces the formal definition of standard spiking neural P systems and some notions which are often used in this area;then, several extensions of the original spiking neural P systems are summarized, that are: Extented SN P system;SN P system with exhaustive use of rules;Asynchronous SN P system;Sequential SN P system. Also, the results on the topic of spiking neural P systems are briefly recalled in two aspects: computational completeness and computational efficiency. In the end, two more important future research directions on spiking neural P systems are pointed out. Specifically, one interesting topic is to develop a new computing model which is more "realistic";another topic is to consider how to use these models in biological modeling and simulation.

关键词： Computational efficiency

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Taming Consistency Distillation for Accelerated Human image Animation

arXiv

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arXiv 2025年

作者： Wang, Xiang Zhang, Shiwei Yuan, Hangjie Wei, Yujie Zhang, Yingya Gao, Changxin Wang, Yuehuan Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Alibaba Group China Fudan University China

Recent advancements in human image animation have been propelled by video diffusion models, yet their reliance on numerous iterative denoising steps results in high inference costs and slow speeds. An intuitive solution involves adopting consistency models, which serve as an effective acceleration paradigm through consistency distillation. However, simply employing this strategy in human image animation often leads to quality decline, including visual blurring, motion degradation, and facial distortion, particularly in dynamic regions. In this paper, we propose the DanceLCM approach complemented by several enhancements to improve visual quality and motion continuity at low-step regime: (1) segmented consistency distillation with an auxiliary light-weight head to incorporate supervision from real video latents, mitigating cumulative errors resulting from single full-trajectory generation;(2) a motion-focused loss to centre on motion regions, and explicit injection of facial fidelity features to improve face authenticity. Extensive qualitative and quantitative experiments demonstrate that DanceLCM achieves results comparable to state-of-the-art video diffusion models with a mere 2-4 inference steps, significantly reducing the inference burden without compromising video quality. The code and models will be made publicly available. Copyright © 2025, The Authors. All rights reserved.

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