Unlike most previous manifold-based data classification algorithms assume that all the data points are on a single manifold, we expect that data from different classes may reside on different manifolds of possible dif...
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Registration of point clouds is required in the processing of large biological data sets. The tradeoff between computation time and accuracy of the registration is the main challenge in this task. We present a novel m...
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A new algorithm, Laplacian MinMax Discriminant Projection (LMMDP), is proposed in this paper for supervised dimensionality reduction. LMMDP aims at learning a discriminant linear transformation. Specifically, we defin...
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This paper proposed a genetic algorithm-based method of path planning for mobile robot in a static environment. The paper uses a simple fitness function as the evaluation standard for an individual or a path. This is ...
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This article considers the limit of a rational Bézier curve. Limits are considered using point-wise, uniform and L1 limits to a family of rational Bézier curves. The paper shows that a rational Bézier c...
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An algorithm for automated extraction of interest points (IP) in hyperspectral images is presented. IP are features of the image that capture information from its neighbors and are distinctive and stable under transla...
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We propose a novel Markovian segmentation model which takes into account edge information. By construction, the model uses only pairwise interactions and its energy is submodular. Thus the exact energy minima is obtai...
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When source signals have nonlinear autocorrelation temporal structure, nonlinear autocorrelation has been used as a statistical property for solving blind source separation (BSS) problem (Z. Shi, Z. Jiang, F. Zhou, A ...
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We developed a simulation tool for investigating the evolution of early metabolism, allowing us to speculate on the formation of metabolic pathways from catalyzed chemical reactions and development of characteristic p...
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ISBN:
(纸本)9780262290753
We developed a simulation tool for investigating the evolution of early metabolism, allowing us to speculate on the formation of metabolic pathways from catalyzed chemical reactions and development of characteristic properties. Our model consists of a protocellular entity with a simple RNA-based genetic system and an evolving metabolism of catalytically active ribozymes that manipulate a rich underlying chemistry. Ensuring an almost open-ended and fairly realistic simulation is crucial for understanding the first steps in metabolic evolution. We show here how our simulation tool can be helpful in arguing for or against hypotheses on the evolution of metabolic pathways. We demonstrate that seemingly mutually exclusive hypotheses may well be compatible when we take into account that different processes dominate different phases in the evolution of a metabolic system. Our results suggest that forward evolution shapes metabolic network in the very early steps of evolution. In later and more complex stages, enzyme recruitment supersedes forward evolution, keeping a core set of pathways from the early phase.
In this paper, we address the reference model adaptive neural network control problem for a class of switched nonlinear singular systems under the case of single input and multiple inputs. Based on RBF neural network,...
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