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Search Results: 1 - 10 of 59041 matches for " Xianyi Yang "
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A multilayer neural network model for perception of rotational motion
Aike Guo,Haijian Sun,Xianyi Yang
Science China Life Sciences , 1997, DOI: 10.1007/BF02879111
Abstract: A multilayer neural nerwork model for the perception of rotational motion has been developed using Reichardt’s motion detector array of correlation type, Kohonen’s self-organized feature map and Schuster-Wagner’s oscillating neural network. It is shown that the unsupervised learning could make the neurons on the second layer of the network tend to be self-organized in a form resembling columnar organization of selective directions in area MT of the primate’s visual cortex. The output layer can interpret rotation information and give the directions and velocities of rotational motion. The computer simulation results are in agreement with some psychophysical observations of rotational perception. It is demonstrated that the temporal correlation between the oscillating neurons would be powerful for solving the “binding problem” of shear components of rotational motion.
Power Factor Analysis of the Linear Motor in Mines
Xianyi Qian
International Journal of Wireless and Microwave Technologies , 2011, DOI: 10.5815/ijwmt.2011.01.04
Abstract: This paper introduces the structure of linear motor in mines. Analyze the power relation of power-AC -linear motor – vibrant machine, based on this, count the power factor; and make mechanical analysis to the vibrancy, get the power factor, which should be: in the precondition of without collision for the top and bottom magnet, do best to decrease the δ_0 to close to ΔΧ_m (ΔΧ_m depends on the technique of the vibrant load), make Κ_δ close to 1 and λ_e close to critical maximum λ_(em) . It is significantly useful to design linear motor.
A hybrid finite difference--finite volume approach to solve first-order hyperbolic conservation laws with superior accuracy
Xianyi Zeng
Computer Science , 2012,
Abstract: A hybrid finite difference--finite volume (FD-FV) approach for discretization in space is proposed to solve first-order hyperbolic conservation laws. Unlike any conventional finite difference method (FDM) or finite volume method (FVM), this approach uses both cell-averaged values and nodal values as degrees of freedom (DOF). Consequently it is inherently conservative like FVM and easy to extend to high-order accuracy in space like FDM. The proposed FD-FV approach works for arbitrary flux functions, whether convex or non-convex; and it does not require any exact or approximate Riemann solver hence it is also computationally economical. Method of lines is adopted for time integration in present work; in particular, explicit Runge-Kutta methods are employed. It is theoretically proven and numerically confirmed that in general, the proposed FD-FV methods possess superior accuracy than conventional FDM or FVM. Linear stability is studied for general FD-FV schemes -- both space-accurate and time-stable FD-FV schemes of up to fifth-order accuracy in both space and time are presented. Numerical examples show that as long as the solutions are smooth, the proposed FD-FV methods are more efficient than conventional FVM of the same order, at least when explicit time-integrators are applied.
A general approach to enhance slope limiters on non-uniform rectilinear grids
Xianyi Zeng
Computer Science , 2013,
Abstract: Most slope limiter functions in high-resolution finite volume methods to solve hyperbolic conservation laws are designed assuming one-dimensional uniform grids, and they are also used to compute slope limiters in computations on non-uniform rectilinear grids. However, this strategy may lead to either loss of total variation diminishing (TVD) stability for 1D linear problems or the loss of formal second-order accuracy if the grid is highly non-uniform. This is especially true when the limiter function is not piecewise linear. Numerical evidences are provided to support this argument for two popular finite volume strategies: MUSCL in space and method of lines in time (MUSCL-MOL), and capacity-form differencing. In order to deal with this issue, this paper presents a general approach to study and enhance the slope limiter functions for highly non-uniform grids in the MUSCL-MOL framework. This approach extends the classical reconstruct-evolve-project procedure to general grids, and it gives sufficient conditions for a slope limiter function leading to a TVD stable, formal second-order accuracy in space, and symmetry preserving numerical scheme on arbitrary grids. Several widely used limiter functions, including the smooth ones by van Leer and van Albada, are enhanced to satisfy these conditions. These properties are confirmed by solving various one-dimensional and two-dimensional benchmark problems using the enhanced limiters on highly non-uniform rectilinear grids.
VISUAL MOTION PERCEPTION BASED ON EMDs ARRAY AND BP NETWORK
基于EMDs阵列和BP网络的视觉运动感知过程

Yang Xianyi,Guo Aike,
杨先一
,郭爱克

生物物理学报 , 1994,
Abstract: In this paper, a visual motinn perception neural network is presented to explore the processing of winal motion information. This model emplops Reichardt's elementary motion detectors array and Rumelhart's BP (learming by back-propagating errors) neural network. In the viewpoint of computational neuroscience, we try to elaborate the nearel mechanism of perception of two dimensional pattern motion from the detection of one dimensional motion component, and answer how the motion vector is represented in the brain. By using computer simulation through a supervised learning process, it is proved that this neural network can solve the "ambiguity" resultal from local inchon deteCtion and give the aCtual orientation, motion direction and motion sped of the pattern.
A SIMPLE BRAIN MODEL FOR THE VISUAL MOTION INFORMATION PERCEPTION
一种感知视觉运动信息的简化脑模型

Yang Xianyi Guo Aike,
杨先一
,郭爱克

生物物理学报 , 1993,
Abstract: The perception of the visual motion information includes the processing from local motion detection to the perception of global pattern movement. Using the neural circuit - network of the figure-ground discrimination of the fly's visual system as the basic unit, and the hexagonal arrays of elementary movement detectors as the input layer, we build a simple brain model for the visual motion information perception. The motion information processing on each layer of this neural computational model is simulated by computer. This model is able to predict correctly the results of differential behavioural experiments. Finally, the neural principles underlying the spatial physiological integration are discussed.
A multilayer neural network model for perception of rotational motion
GUO Aike,SUN Haijian,YANG Xianyi,
郭爱克
,孙海坚,杨先一

中国科学C辑(英文版) , 1997,
Abstract: A multilayer neural nerwork model for the perception of rotational motion has been developed usingReichardt's motion detector array of correlation type, Kohonen's self-organized feature map and Schuster-Wagner's oscillating neural network. It is shown that the unsupervised learning could make the neurons on the second layer of the network tend to be self-organized in a form resembling columnar organization of selective directions in area MT of the primate's visual cortex. The output layer can interpret rotation information and give the directions and velocities of rotational motion. The computer simulation results are in agreement with some psychophysical observations of rotation-al perception. It is demonstrated that the temporal correlation between the oscillating neurons would be powerful for solving the "binding problem" of shear components of rotational motion.
ADAPTIVE PROBABILITIES OF SELECTION,CROSSOVER AND MUTATION IN GENETIC ALGORITHMS
自适应复制、交叉和突变的遗传算法

Yang Zhenqiang,Wang Changhong,Zhuang Xianyi,
杨振强
,王常虹,庄显义

电子与信息学报 , 2000,
Abstract: In this paper an adaptive genetic algorithms is presented. The adaptive method of probabilities of reproduction, crossover, and mutation which have selectivity about the operated solutions is adopted in the course of calculation. It makes the reproduction probability of the solution which has the similar fitness decrease, the probabilities of crossover and mutation increase, hence it maintains the diversity in the population and sustains the search capacity of the genetic algorithms. The method is tested by the genetic algorithm testing functions. The results are excellent.
企业社会责任对消费者购买意向的影响研究
A Study of the Influence of the CSR on Consumers’ Purchase Intention

邓新明,张婷,许洋,龙贤义
DENG Xinming
,ZHANG Ting,XU Yang,LONG Xianyi

- , 2016,
Abstract: 摘要 为了探究企业社会责任对消费者购买意愿的影响机制,构建了一个包含企业社会责任、动机归因、消费者购买意愿、消费者利他倾向、企业社会责任-企业能力信念在内的研究框架,并通过问卷调查的方法对概念模型进行了实证检验。研究结果表明:企业社会责任不仅对消费者购买意愿产生直接正向影响,而且通过动机归因对消费者购买意愿产生间接正向影响;企业社会责任对动机归因的影响过程受到了消费者利他倾向的正向调节作用;动机归因和消费者购买意愿之间的关系受到了企业社会责任-企业能力信念的负向调节作用
Dynamical Properties in a Fourth-Order Nonlinear Difference Equation
Yunxin Chen,Xianyi Li
Advances in Difference Equations , 2010, DOI: 10.1155/2010/679409
Abstract: The rule of trajectory structure for fourth-order nonlinear difference equation xn+1=(xan 2+xn 3)/(xan 2xn 3+1), n=0,1,2,…, where a∈[0,1) and the initial values x 3,x 2,x 1,x0∈[0,∞), is described clearly out in this paper. Mainly, the lengths of positive and negative semicycles of its nontrivial solutions are found to occur periodically with prime period 15. The rule is 4+,3 ,1+,2 ,2+,1 ,1+, 1 in a period. By utilizing this rule its positive equilibrium point is verified to be globally asymptotically stable.
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