P systems are a class of distributed and parallel computing models inspired by the structure and the functioning of a single cell and complexes of cells. The computational efficiency of P systems with active membranes...
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P systems are a class of distributed and parallel computing models inspired by the structure and the functioning of a single cell and complexes of cells. The computational efficiency of P systems with active membranes has been investigated widely with the assumption that the application of rules is completed in exactly one time unit. However, in biological facts, different biological processes may take different times to complete, and the execution time of certain biological process could vary because of external uncontrollable conditions. With this biological motivation, in this work, we solve SAT problem by a family of P systems with active membranes in a time-free manner in the sense that the correctness of the solution does not depend on the precise timing of the involved rules. In such a solution, standard cell division rules for elementary membranes are applied: the newly generated membranes have the same label with their parent membrane. This result answers an open problem formulated in Song et al. (Theor Comput Sci 529:61-68, 2014).
P systems are a class of computational models inspired by the structure and the functioning of a living cell. In the semantics of P systems, there exists a global clock, which marks the time for the system, and the ex...
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P systems are a class of computational models inspired by the structure and the functioning of a living cell. In the semantics of P systems, there exists a global clock, which marks the time for the system, and the execution time of each rule takes exactly one time unit. However, in living cells, the execution time of different biochemical reactions is dependent on many uncontrollable factors, and it is hard to know precisely the specific execution time of a reaction. In this work, with this biological inspiration, we consider the class of P systems with active membranes that are "robust" against the execution time of rules. Specifically, we give a time-free uniform solution to the SAT problem using P systems with active membranes, where the constructed P system can solve a family of instances with an arbitrarily given size, and the execution time of the involved rules has no influence on the correctness of the solution. We also prove that any Turing computable set of numbers can be generated by a time-free P system with active membranes in the sense that the set of numbers generated by the given P system with active membranes does not depend on the execution time of rules. (C) 2014 Elsevier B.V. All rights reserved.
Existing retinex-based low-light image enhancement strategies focus heavily on crafting complex networks for Retinex decomposition but often result in imprecise estimations. To overcome the limitations of previous met...
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Existing retinex-based low-light image enhancement strategies focus heavily on crafting complex networks for Retinex decomposition but often result in imprecise estimations. To overcome the limitations of previous methods, we introduce a straightforward yet effective strategy for Retinex decomposition, dividing images into colormaps and graymaps as new estimations for reflectance and illumination maps. The enhancement of these maps is separately conducted using a diffusion model for improved restoration. Furthermore, we address the dual challenge of perturbation removal and brightness adjustment in illumination maps by incorporating brightness guidance. This guidance aids in precisely adjusting the brightness while eliminating disturbances, ensuring a more effective enhancement process. Extensive quantitative and qualitative experimental analyses demonstrate that our proposed method improves the performance by approximately 4.4% on the LOL dataset compared to other state-of-the-art diffusion-based methods, while also validating the model's generalizability across multiple real-world datasets.
Continuous ambulatory blood pressure (ABP) records may be an important independent determinant to the better prevention and diagnosis of cardiovascular disease. The purpose of this study is to develop and validate a n...
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Continuous ambulatory blood pressure (ABP) records may be an important independent determinant to the better prevention and diagnosis of cardiovascular disease. The purpose of this study is to develop and validate a novel application of independent component analysis (ICA) based auto-regression forecasting model (ICA-ARF) to noninvasively, continuously and conveniently derive ABP from the radial artery pressure waveform (RAPWF) in humans. RAPWF is acquired using a pressure transducer worn on the wrist, so it may perturbed by many factors, such as the tightness of wrist strap, the location of sensor and so on. To eliminate the effect of correlativity among measurement factors, ICA method is used to decompose the raw signal and extract the independent component which is affected by blood pressure (BP) only. Based on the spectrum density of independent component, an auto-regression forecasting model is set up to derive BR An experiment to validate the prediction model is done and the results show an excellent correlation and agreement between directly measured BP which is measured by Omron electronic BP monitor (Type: HEM-7012). When the ICA-ARF is used, the error reduces from 7.4 mmHg to 2.55 mmHg. The novel methods have important implications for the simplification of noninvasive CASP measurement and 24-hour ambulatory BP monitoring and assessment of central aortic blood pressure.
Spiking neural P systems with astrocytes (SNPA systems, for short) are a class of distributed parallel computing devices inspired from the way spikes pass along the synapses between neurons. In this work, we investiga...
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Spiking neural P systems with astrocytes (SNPA systems, for short) are a class of distributed parallel computing devices inspired from the way spikes pass along the synapses between neurons. In this work, we investigate the computational power of SNPA systems as language generators. Specifically, representations of recursively enumerable languages and of regular languages are given by means of SNPA systems without forgetting rules. Furthermore, a simple finite language is produced which can be generated by SNPA systems, while it cannot be generated by usual spiking neural P systems. These results show that the astrocytes are a powerful ingredient for spiking neural P systems as language generators.
This paper is considered with the computation of upper bounds for the solution of continuous algebraic Riccati equations (CARE). A parameterized upper bound for the solution of CARE is proposed by utilizing some linea...
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This paper is considered with the computation of upper bounds for the solution of continuous algebraic Riccati equations (CARE). A parameterized upper bound for the solution of CARE is proposed by utilizing some linear algebraic techniques. Based on this bound, more precise estimation can be achieved by means of carefully choosing the bound's parameters. Iterative algorithm is also developed to obtain more sharper solution bounds. Comparing with some existing results in the literature, the proposed bounds are less restrictive and more effective. The effectiveness and advantages of the proposed approach are illustrated via a numerical example.
This article proposes a new cooperation framework of energy storage sharing that comprises prosumers, energy storage providers (ESPs), and a middle agent to achieve social energy optimality. In this framework, the pro...
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This article proposes a new cooperation framework of energy storage sharing that comprises prosumers, energy storage providers (ESPs), and a middle agent to achieve social energy optimality. In this framework, the prosumers share multiple energy storages of the ESPs via the agent. An energy sharing optimization problem minimizing the total energy cost is formulated involving the energy storage operation, the shiftable load schedule, and the energy trading with the utility. To solve the problem, a fast alternating direction multiplier method (ADMM) with restart which converges faster than traditional ADMM is adopted. Furthermore, a clearing scheme, named as an ideal profit realization ratio distribution model is introduced to distribute the participants' net profits fairly. Simulation results show that the energy costs can be substantially reduced, and the net profit distribution is relatively fairer compared with the widely used Nash bargaining scheme, which ensures the feasibility of our framework in real applications.
The slow power tracking, operating safety, especially the fuel exhaustion, and high efficiency considerations are the key issues for integrated solid oxide fuel cell (SOFC) systems during power step up transients, res...
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The slow power tracking, operating safety, especially the fuel exhaustion, and high efficiency considerations are the key issues for integrated solid oxide fuel cell (SOFC) systems during power step up transients, resulting in the relatively poor dynamic capabilities and make the transient load following very challenging and must be enhanced. To this end, this paper first focus on addressing the efficiency optimization associated with simultaneous power and thermal management of a 5-kW SOFC system. Particularly, a traverse optimization process including cubic convolution interpolation algorithm are proposed to obtain optimal operating points (OOPs) with the maximum efficiency. Then this paper investigate the current implications on system step-up transient performance, then a two stage preconditioning current strategy and a feedback power reference control scheme is proposed for load stepup transients to balance fast load following and fuel starvation, after that safe thermal transient is validated. Simulation results show the efficacy of the control design by demonstrating the fast load following ability while maintaining the safe operation, thus safe;efficient and fast load transition can be achieved. (C) 2015 Elsevier Ltd. All rights reserved.
In this article, a distributed secondary controller is proposed for an islanded DC microgrid to preserve privacy information of the local power sources, while achieving current sharing among the generators and voltage...
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In this article, a distributed secondary controller is proposed for an islanded DC microgrid to preserve privacy information of the local power sources, while achieving current sharing among the generators and voltage regulation of the DC bus. Based on the state decomposition mechanism, the original secondary control signal of each generator is decomposed into two parts: one takes over the role of communicating with neighbors, while the other affects the evolution of the former one and is invisible to the neighbors. Besides, random noises are introduced to mask the true value of the transmitted signals. Under the proposed controller, the current data of the local generators can be kept confidential, as well as the associated privacy power information. In this way, the power security risks caused by privacy information leakage can be avoided. Lastly, both simulation and experiment tests are imposed to verify the effectiveness of the proposed control scheme.
Cell-like spiking neural P systems are a variant of standard spiking neural P systems, which have a cell-like instead of neural-like architecture. It has been proved that cell-like spiking neural P systems can generat...
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Cell-like spiking neural P systems are a variant of standard spiking neural P systems, which have a cell-like instead of neural-like architecture. It has been proved that cell-like spiking neural P systems can generate Turing computable sets of numbers. In this work, the computational power of cell-like spiking neural P systems as language generators is investigated. Characterization of finite languages is obtained with cell-like spiking neural P systems when the number of spikes produced is less than the number of spikes consumed, and characterization of recursively enumerable languages is obtained by cell-like spiking neural P systems when there is no restriction on the number of produced spikes. The relationships of the languages generated by cell-like spiking neural P systems with regular, non-context-free and non-semilinear languages are also investigated.
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