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self organizing competitive
相关语句
  自组织竞争
     On this basis, the regional category of working day norm of construction is divided respectively by applying the clustering function of self organizing competitive networks and Matlab 6.1 software programming and 2~9 category division.
     应用自组织竞争网络的聚类功能、Matlab 6 .1软件编程和 2~ 9类区分法 ,分别划分出建设工期定额的地域类别 .
短句来源
     The semiconductor gas sensors sensitive to hydrogen and carbon monoxide are chosen to compose the gas sensor array,and an on-line data acquisition system is constructed,which is combined with the pattern recognition techniques of self organizing competitive network for the research of gas qualitative analysis.
     优选了分析H2,CO气体的半导体气体传感器组成阵列,建立了实时数据采集系统,并与自组织竞争网络模式识别技术相结合,以进行气体定性分析的研究;
短句来源
  相似匹配句对
     Outline for Self organizing Methodology
     自组织方法论论纲
短句来源
     Self-organizing Information of Life
     生命自组织信息
短句来源
     On the Competitive Engagement
     刍议竞争上岗
短句来源
     On Competitive Readiness
     再论竞技状态
短句来源
     On Mathematics Competitive
     也谈数学的竞技性
短句来源
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  self organizing competitive
The network is trained by the self-organizing competitive learning algorithm.
      
These self-organizing competitive processes create the circumstances important for the growth of effective governance.
      
Each layer is considered to act partly as a set of local self-organizing competitive neuronal networks with overlapping inputs.
      
At each stage or layer the self-organizing competitive nets would result in combinations of inputs becoming the effective stimuli for neurons.
      


In this paper, a new algorithm based on a supervised selforganizing neural network for the passive sonar target recognition was proposed. Because of the incompletement of the passive sonar sampling pattern set, this algorithm introduced a mult i-active-function struct ure and self-organizing competitive learning algorithm into the classic feed-forward neural network, and obviously improved the generalization ability of target recognition. Besides, it can efficiently reduce the learning time...

In this paper, a new algorithm based on a supervised selforganizing neural network for the passive sonar target recognition was proposed. Because of the incompletement of the passive sonar sampling pattern set, this algorithm introduced a mult i-active-function struct ure and self-organizing competitive learning algorithm into the classic feed-forward neural network, and obviously improved the generalization ability of target recognition. Besides, it can efficiently reduce the learning time andavoided the local optimum. The recognition experiments of real passive sonar signals say that this new algorithm has good generalization ability and high recognition rate.

针对水声信号的特性和无源声呐目标识别的特点,提出了一种有师自组织神经网络分类算法。该算法主要针对水声信号的样本不完备的问题,在前债神经网络中引入了多重神经元激活模型和自组织竞争学习算法,使无源声呐分类系统的泛化性能有了明显的提高。该算法采用分层学习策略,有效地节省了训练时间,同时减少了陷入局部最优解的概率。通过对实录海上无源声呐目标信号的分类实验,检验了算法的识别能力和泛化能力,实验结果责明该算法具有良好的泛化能力同时保持了较高的识别率.

This paper proposes an edge detection of globular material using neural networks. It includes the extraction of edge pixel candidates and edge detection using neural networks. The neural network consists of self-organizing competitive subnet used for image compressing and image encoding, and the radial basis function subnet used for deducing edge vectors. The tests showed that images segmented by this method have good edge closedness and true edge and are suitable for the segmentation of the...

This paper proposes an edge detection of globular material using neural networks. It includes the extraction of edge pixel candidates and edge detection using neural networks. The neural network consists of self-organizing competitive subnet used for image compressing and image encoding, and the radial basis function subnet used for deducing edge vectors. The tests showed that images segmented by this method have good edge closedness and true edge and are suitable for the segmentation of the cumulate particle image.

针对颗粒图像的特点,提出一种基于神经网络的边缘混合检测方法。该方法包含边界候选象素提取和神经网络边缘检测两部分,神经网络由用于图像信息压缩与图像信息编码的自组织竞争子神经网络(ASCSNN)和用于获取图像边缘矢量信息的基于径向函数子神经网络(RBFSNN)组成。实验结果表明,该方法分割颗粒图像得到的边缘图像封闭性好、边界描述真实,适用于堆积颗粒物料图像的边缘检测。

This paper proposes an edge detection method of globular material using hybrid neural network. The proposed network consists of self-organizing competitive netal network used for feature extraction from the binary input pattern of the dge candidates image and the BP network network used for deducing edge vectro and a logical judgement algorithm is used for getting edge candidate image' Edge pixel pixel scandidates and its neighbor pixels constitUte the binary samples of the hybrid neural network....

This paper proposes an edge detection method of globular material using hybrid neural network. The proposed network consists of self-organizing competitive netal network used for feature extraction from the binary input pattern of the dge candidates image and the BP network network used for deducing edge vectro and a logical judgement algorithm is used for getting edge candidate image' Edge pixel pixel scandidates and its neighbor pixels constitUte the binary samples of the hybrid neural network. The expermments on image corrupted with Gaussian noise show that the image segmented by this method has good edge closedness and true edge and are suitable for the segmentation of the cumulate particle image.

本文提出了一种应用混合神经网络进行颗粒图像检测的方法。混合神经网络由用于对边缘候选图像的二值输入模式进行聚类特征提取的自组织竞争子网络(ASCSNN)和用于获取颗粒图像边缘矢量信息的BP子网络(BPSNN)组成,边缘候选图像是通过采用基于灰度极小值算法提取的边缘候选象素获得。神经网络以边缘候选图像中的边缘候选象素及其邻域象素的二值模式作为训练样本。对经过噪声污染的图像进行实验表明,该方法获得的边缘图像封闭性好、边缘描述真实,抗干扰能力较强,适用于颗粒图像的边缘检测。

 
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