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 estimat...
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In order to identify multi micro objects, an improved support vector machine algorithm is present, which employs invariant moments based edge extraction to obtain feature attribute and then presents a heuristic attrib...
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The problem of finding small universal spiking neural P systems was recently investigated by Andrei Paun and Gheorghe Paun, for spiking neural P systems used as devices computing functions and as devices generating se...
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The problem of finding small universal spiking neural P systems was recently investigated by Andrei Paun and Gheorghe Paun, for spiking neural P systems used as devices computing functions and as devices generating sets of numbers. For the first case, a universal spiking neural P system was produced by using 84 neurons for standard rules and using 49 neurons for extended rules. For spiking neural P systems used as generators of sets of numbers, a universal system with standard rules having 76 neurons, and one with extended rules having 50 neurons were obtained. In this paper, we continue the study of small universal spiking neural P systems and we improve in the number of neurons as follows. The small universal spiking neural P systems use 67 neurons for standard rules and 41 neurons for extended rules in the case of computing functions, and 63 neurons for standard rules and 41 neurons for extended rules in the case of generating sets of numbers.
Disasters cause tremendous damage every year. In this paper, we have specifically studied emergency response to disaster-struck scale-free networks when some nodes in the network have redundant systems. If one node co...
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Disasters cause tremendous damage every year. In this paper, we have specifically studied emergency response to disaster-struck scale-free networks when some nodes in the network have redundant systems. If one node collapses, its redundant system will substitute it to work for a period of time. In the first part, according to the network structure, several redundant strategies have been formulated, and then our studies focused on their effectiveness by means of simulation. Results show that the strategy based on total degrees is the most effective one. However, many nodes still collapse in the end if redundant systems do not have sufficient capability, so emergency responses are necessary. Several emergent strategies controlling the distribution of external resources have been proposed in the second part. The effectiveness of those emergent strategies are then studied from three aspects, such as the effect of strategies on spreading processes, minimum sufficient quantities of external resources and determination of the most appropriate emergent strategy. In addition, the effects of redundant intensity on these aspects have been discussed as well. (C) 2008 Elsevier B.V. All rights reserved.
We proposed recently the computation of epileptic connectivity graphs based on wavelet correlation coefficients between EEG signals. The suspected epileptiform electrodes are recognized using the clustering of the top...
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We proposed recently the computation of epileptic connectivity graphs based on wavelet correlation coefficients between EEG signals. The suspected epileptiform electrodes are recognized using the clustering of the topological properties of the graph that can be useful for pre-surgical studies. Here, we present a method for comparing epileptic networks estimated from scalp and intracranial EEG (IEEG) in partial epilepsy patients. The results are presented for a patient with left temporal epilepsy. Good spatial correspondence between the IEEG and the scalp EEG epileptic graphs is obtained. These results are consistent with the patient's clinical diagnosis.
Several neutrosophic combination rules based on the Dempster-Shafer theory (DST) and Dezert-Smarandache theory (DSmT) are presented in this study. The new information fusing approaches proposed the neutrosophic belief...
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For biogroups and groups of self-driven agents, making decisions often depends on interactions among group members. In this paper, we seek to understand the fundamental predictive mechanisms used by group members in o...
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For biogroups and groups of self-driven agents, making decisions often depends on interactions among group members. In this paper, we seek to understand the fundamental predictive mechanisms used by group members in order to perform such coordinated behaviors. In particular, we show that the future dynamics of each node in the network can be predicted solely using local information provided by its neighbors. Using this predicted future dynamics information, we propose a decentralized predictive consensus protocol, which yields drastic improvements in terms of both consensus speed and internal communication cost. In natural science, this study provides an evidence for the idea that some decentralized predictive mechanisms may exist in widely-spread biological swarms/flocks. From the industrial point of view, incorporation of a decentralized predictive mechanism allows for not only a significant increase in the speed of convergence towards consensus but also a reduction in the communication energy required to achieve a predefined consensus performance. Copyright (C) EPLA, 2009
We continue the study of (extended) spiking neural P systems with exhaustive use of rules by considering these computing devices as language generators. Specifically, a step is associated with a symbol according to th...
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The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, ...
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The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, which can satisfy certain combinatorial and thermodynamic constraints. Using taboo search algorithm, our method can avoid trapping into local optimization and can nd a set of good DNA sequences satisfying required constraints.
By introducing a predictive mechanism with small-world connections, we propose a new motion protocol for self-driven flocks. The small-world connections are implemented by randomly adding long-range interactions from ...
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By introducing a predictive mechanism with small-world connections, we propose a new motion protocol for self-driven flocks. The small-world connections are implemented by randomly adding long-range interactions from the leader to a few distant agents, namely, pseudoleaders. The leader can directly affect the pseudoleaders, thereby influencing all the other agents through them efficiently. Moreover, these pseudoleaders are able to predict the leader’s motion several steps ahead and use this information in decision making towards coherent flocking with more stable formation. It is shown that drastic improvement can be achieved in terms of both the consensus performance and the communication cost. From the engineering point of view, the current protocol allows for a significant improvement in the cohesion and rigidity of the formation at a fairly low cost of adding a few long-range links embedded with predictive capabilities. Significantly, this work uncovers an important feature of flocks that predictive capability and long-range links can compensate for the insufficiency of each other. These conclusions are valid for both the attractive and repulsive swarm model and the Vicsek model.
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