Self Organizing Map is a method of artificial neural network, which implements pattern recognition and data clustering simultaneously.
自组织特征映射是一种人工神经网络方法，可以同时实现模式识别和数据分类。
This paper presents a hierarchical self organizing neural network model and its application in the learning of the trajectory distribution patterns for event recognition.
提出一个层次自组织神经网络模型，并将其应用于基于事件识别的轨迹分布模式学习中。
A speech recognition method, which is based on self-organizing neural networks is presented.
建立了一种基于自组织神经网络的语音识别系统。
Self organizing feature map (SOM) network can extract the internal features of parameter by self organizing and reflect them on the classified map. It can be used in problems of pattern recognition.
自组织特征映射(SOM)神经网络能通过自组织有效地提取出各特征参数间的内在特征并映射到分类模板上，它可以用于各种模式识别问题。
This paper presents a hierarchical self organizing neural network model and its application in the learning of the trajectory distribution patterns for event recognition.
这里介绍一种利用自组织神经网络识别曲线形态的方法。
A method that applies the clustering function of SOFM (Self-Organizing Feature Maps) network is proposed for autonomous star pattern recognition.
介绍了一种利用自组织特征映射(SOFM)网络的聚类功能进行全天星图识别的方法。
An autonomous star pattern recognition method using the tri-star clustering function of SOFM (Self-Organizing Feature Maps) network is described.
介绍了一种利用SOFM(自组织特征映射)网络的聚类功能进行全天星图识别的算法。
Self-organizing neural network is a very efficient method for pattern recognition and vector quantization(VQ).
为有效提高矢量量化码书的性能和学习效率，需进一步改进自组织神经网络的学习算法。
A speech recognition method, which is based on self-organizing neural networks is presented.
这里介绍一种利用自组织神经网络识别曲线形态的方法。
A speech recognition method, which is based on self-organizing neural networks is presented.
这里介绍一种利用自组织神经网络识别曲线形态的方法。
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