Spiking neural P systems are a class of dis- tributed parallel computing models inspired from the way neurons communicate with each other by means of electri- cal impulses (called "spikes"). In this paper, w...
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Spiking neural P systems are a class of dis- tributed parallel computing models inspired from the way neurons communicate with each other by means of electri- cal impulses (called "spikes"). In this paper, we continue the research of normal forms for spiking neural P systems. Specifically, we prove that the degree of spiking neural P systems without delay can be decreased to two without losing the computational completeness (both in the gener- ating and accepting modes).
作者：
Sun, YangguangDing, MingyueCollege of Computer Science
South-Central University for Nationalities State Key Laboratory of Software Engineering Wuhan University Wuhan 430074 China School of Life Science and Technology
'Image Processing and Intelligence Control' Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China
A route planning method based on gradient-field quantum genetic algorithm model was presented in this paper. It introduces the gradient field of a grid map to quantum genetic algorithm model and uses quantum genetic a...
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This paper is to present a defect detecting and locating method of tubular cylindrical conductor based on alternating current impedance measurement theory. A defect estimation can be made through the impedance measure...
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This paper addresses the stability and stabilization problems for a class of positive linear systems in the presence of saturating actuators. The objective is to give conditions of the stability, and design state feed...
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This paper addresses the stability and stabilization problems for a class of positive linear systems in the presence of saturating actuators. The objective is to give conditions of the stability, and design state feedback control laws such that the closed-loop systems is asymptotically stable and positive at the origin with a large domain of attraction. Several sufficient conditions for stabilization and positivity are derived via the Lyapunov functions method and convex analysis in both the continuous-time and the discrete-time cases, respectively. The state feedback controller design and the estimation of domain of attraction are presented by solving a convex optimization problem with LMIs constraints. A numerical example is given to show the effectiveness of the proposed methods.
Presently pneumatic muscles (PMs) are used in various applications due to their simple construction, lightweight and high force to weight ratio. However, pneumatic muscles are facing various problems due to their nonl...
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In this paper, an optimal guidance algorithm is proposed for atmospheric ascent. The optimal guidance algorithm updates the reference trajectory to deal with the impact of disturbance by solving an optimal control pro...
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In this paper, the Pneumatic Muscle (PM) as actuator is investigated. The PM model is established by using a phenomenological model consisting of a contractile element, a spring element, and a damping element in paral...
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Pneumatic muscle (PM) has strong time varying characteristic. The complex nonlinear dynamics of PM system poses problems in achieving accurate modeling and control. To solve these challenges, we propose an echo state ...
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Target detecting algorithm in infrared image is drawing extensive attention both at home and abroad, expecially when the infrared images own complex backgrounds and low resolution. How to make sure of the accuracy of ...
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It is difficult to guide the entry vehicle to prescribed area due to the disperse of environment and kinematics. Through predicted residual range at the current state based on drag acceleration, we developed a predict...
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