多相空间数值模拟并行化研究

This paper researches on parellelization of multiphase space numerical simulation with the case of the gaskinetic algorithm for 3-D flows. It focuses on the techniques of domain decomposition methods, vector reduction andboundary processing parallel optimization. The HPF parallel program design has been developed by the Parallel Pro-gramming Concept Design (PPCDS). The preferable parallel efficiency has been found by the HPF program in highperformance computer with massive scale parallel computing.

多相空间矢量脉宽调制技术研究

近年来 ,三臂三相空间矢量脉宽调制 (SVPWM)逆变器在三相交流电机变频调速中得到了广泛的应用。但三臂三相SVPWM难于胜任大转速—力矩调节范围、大功率、高可靠性的要求。本文对三相SVPWM技术进行推广 ,提出并分析一种多臂多相的空间矢量脉宽调制和极相调制技术。特别地 ,将 9相SVPWM技术应用到九绕组感应电机中 ,并将 9相SVPWM技术与

多相水平集协同空间模糊聚类图像多目标分割

图像多目标分割的研究对于机器视觉发展具有重要意义。多相水平集模型(Multiphase level set,MLS)对零水平集函数初始位置和噪声敏感,当初始位置不适宜、噪声较大时无法准确分割多目标。针对上述问题,提出一种多相水平集模型协同空间模糊C-均值聚类(Spatial fuzzy C-means,SFCM)的图像多目标分割算法,即SFCM-MLS算法。首先用空间模糊聚类获取图像多目标粗分割结果,然后用粗分割结果定义多相水平集模型的初始水平集函数对图像做精分割。针对人脑磁共振成像(Magnetic resonance imaging,MRI)图像和患有肿瘤的肝脏计算机扫描断层图像多目标分割试验结果表明,与经典多相水平集模型相比,SFCM-MLS算法对初始位置不敏感,提高了图像多目标分割的准确性。

Local polynomial prediction method of multivariate chaotic time series and its application

To improve the prediction accuracy of chaotic time series, a new methodformed on the basis of local polynomial prediction is proposed. The multivariate phase spacereconstruction theory is utilized to reconstruct the phase space firstly, and on its basis, apolynomial function is applied to construct the prediction model, then the parameters of the modelaccording to the data matrix built with the embedding dimensions are estimated and a one-stepprediction value is calculated. An estimate and one-step prediction value is calculated. Finally,the mean squared root statistics are used to estimate the prediction effect. The simulation resultsobtained by the Lorenz system and the prediction results of the Shanghai composite index show thatthe local polynomial prediction errors of the multivariate chaotic time series are small and itsprediction accuracy is much higher than that of the univariate chaotic time series.

Understanding visual-auditory correlation from heterogeneous features for cross-media retrieval

Cross-media retrieval is an interesting research topic,which seeks to remove the barriers among different modalities.To enable cross-media retrieval,it is needed to find the correlation measures between heterogeneous low-level features and to judge the semantic similarity.This paper presents a novel approach to learn cross-media correlation between visual features and auditory features for image-audio retrieval.A semi-supervised correlation preserving mapping(SSCPM)method is described to construct the isomorphic SSCPM subspace where canonical correlations between the original visual and auditory features are further preserved.Subspace optimization algorithm is proposed to improve the local image cluster and audio cluster quality in an interactive way.A unique relevance feedback strategy is developed to update the knowledge of cross-media correlation by learning from user behaviors,so retrieval performance is enhanced in a progressive manner.Experimental results show that the performance of our approach is effective.

Similarity Reductions of(2+1)-Dimensional Multi-component Broer-Kaup System

Painleve property of the （2＋1）-dimensional multi-component Broer-Kaup （BK） system is considered by using the standard Weiss Kruskal approaches. Applying the Clarkson and Kruskal （CK） direct method to the （2＋1）- dimensional multi-component BK system, some types of similarity reductions are obtained. By solving the reductions, one can get the solutions of the （2＋1）-dimensional multi-component BK system.

Spatial Correlation and Ecological Characteristics Analysis of Man-agement Area for Biodiversity Conservation and Relevant Regionalization

Formulation of different ecological zone plans according to the corresponding protection targets and the necessity of proper conservation policy is one of the measures to achieve the goal of ecological conservation in China.In order to clarify the interrelation among key ecological zone plans,this paper carried out the research on spatial relation of priority areas of biodiversity conservation and three key ecological areas(key ecological function areas,key regions of ecological service function,national nature reserves)and the research on ecological conditions,based on multi-scale ecological spatial theme information,which incorporates elements like ecological quality and type,and by the aid of spatial information analysis and GIS modeling.The results showed a contrastively fine spatial consistency with 68.8%of priority areas of biodiversity conservation overlapping with three key ecological areas.Although the environment in priority areas of biodiversity conservation were in good conditions,protection pressure is also increasing,powerful supervision and protection should not be ignored.The environmental conditions in the overlapping areas,as a whole,were superior to those in the non-overlapping areas.Since two areas have different characteristics,targeted protection measures should be formulated based on this difference,which will be very important for biodiversity conservation in priority areas of biodiversity conservation.

Multi-scale prediction of MEMS gyroscope random drift based on EMD-SVR

To improve the prediction accuracy of micro-electromechanical systems(MEMS)gyroscope random drift series,a multi-scale prediction model based on empirical mode decomposition(EMD)and support vector regression(SVR)is proposed.Firstly,EMD is employed to decompose the raw drift series into a finite number of intrinsic mode functions(IMFs)with the frequency descending successively.Secondly,according to the time-frequency characteristic of each IMF,the corresponding SVR prediction model is established based on phase space reconstruction.Finally,the prediction results are obtained by adding up the prediction results of all IMFs with equal weight.The experimental results demonstrate the validity of the proposed model in random drift prediction of MEMS gyroscope.Compared with a single SVR model,the proposed model has higher prediction precision,which can provide the basis for drift error compensation of MEMS gyroscope.

Fundamental Theories of Spatial Similarity Relations in Multi-scale Map Spaces

Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from images, and the description of spatial features on maps.However, little achievements have been made for it by far.In this paper, spatial similarity relation was put forward with the introduction of automated map generalization in the construction of multi-scale map databases;then the definition of spatial similarity relations was presented based on set theory, the concept of spatial similarity degree was given, and the characteristics of spatial similarity were discussed in detail, in-cluding reflexivity, symmetry, non-transitivity, self-similarity in multi-scale spaces, and scale-dependence.Finally a classification system for spatial similarity relations in multi-scale map spaces was addressed.This research may be useful to automated map generalization, spatial similarity retrieval and spatial reasoning.

Complementarity Problems for Multivalued Non-Monotone Operators in Banach Spaces

We utilize Park＇s maximal element theorem in H-space to prove the existence theorems of solutions of the complementarity problems for multivalued non-monotone operators in Banach spaces.

Parameter Diversity Induced Multiple Spatial Coherence Resonances and Spiral Waves in Neuronal Network with and Without Noise

Diversity in the neurons and noise are inevitable in the real neuronal network.In this paper,parameter diversity induced spiral waves and multiple spatial coherence resonances in a two-dimensional neuronal network without or with noise are simulated.The relationship between the multiple resonances and the multiple transitions between patterns of spiral waves are identified.The coherence degrees induced by the diversity are suppressed when noise is introduced and noise density is increased.The results suggest that natural nervous system might profit from both parameter diversity and noise,provided a possible approach to control formation and transition of spiral wave by the cooperation between the diversity and noise.

Tomographic TR-PIV measurement of coherent structure spatial topology utilizing an improved quadrant splitting method

In this paper,we calculated the spatial local-averaged velocity strains along the streamwise direction at four spatial scales according to the concept of spatial local-averaged velocity structure function by using the three-dimensional three-component database of time series of velocity vector field in the turbulent boundary layer measured by tomographic time-resolved particle image velocimetry.An improved quadrant splitting method,based on the spatial local-averaged velocity strains together with a new conditional sampling phase average technique,was introduced as a criterion to detect the coherent structure topology.Furthermore,we used them to detect and extract the spatial topologies of fluctuating velocity and fluctuating vorticity whose center is a strong second-quadrant event(Q2) or a fourth-quadrant event(Q4).Results illustrate that a closer similarity of the multi-scale coherent structures is present in the wall-normal direction,compared to the one in the other two directions.The relationship among such topological coherent structures and Reynolds stress bursting events,as well as the fluctuating vorticity was discussed.When other burst events are surveyed(the first-quadrant event Q1 and the third-quadrant event Q3),a fascinating bursting period circularly occurs:Q4-S-Q2-Q3-Q2-Q1-Q4-S-Q2-Q3-Q2-Q1 in the center of such topological structures along the streamwise direction.In addition,the probability of the Q2 bursting event occurrence is slightly higher than that of the Q4 event occurrence.The spatial instable singularity that almost simultaneously appears together with typical Q2 or Q4 events has been observed,which is the main character of the mutual induction mechanism and vortex auto-generation mechanism explaining how the turbulence is produced and maintained.

Spectral spatial coherence of high-power multi-chip LEDs

We investigate the spatial coherence of the light generated from high-power multi-chip red LEDs by usmg the van Cittert- Zernike theorem. It is theoretically demonstrated that the light generated from multi-chip LEDs evolves into partially coherent light after propagation, and the spatial coherence is increased with the increase of propagation distance. Moreover, the spatial coherence of the light is found to be closely related to the chip distribution of multi-chip LEDs. The distribution of the spatial coherence of the light is experimentally examined by Young＇s double-slit interference. It is found that the experimental results are consistent with the theoretical ones.