研究了基于自适应特征融合及模块神经网络的手写体汉字识别。
I studied the handwritten Chinese character recognition techniques based on adaptive information fusion and module neural networks.
数据融合方法采用经典的自适应加权融合估计算法，配合智能判别技术，增强了火灾特征识别的可靠性。
Combined with intelligent recognition technology, data fusion technology adopts the classical self-adapting weighting fusion algorithm to increase the reliability of fire characteristics recognition.
并将两种特征模型进行线性融合，得到最终的目标表征模型，其中的融合系数由特征似然图对比度自适应确定。
The final target representation model was obtained by means of linear fusing the two feature models, and the fusion coefficient was determined adaptively by contrast ratio of feature likelihood map.
继而研究了模糊artmap网络用于特征层融合识别的方法，并提出了一种网络警戒参数自适应调整新算法。
Next the general method of applying fuzzy ARTMAP model to feature level fusion is also expounded and we put forward a learning algorithm with adaptive vigilance parameters for each cluster.
为了对不同的多聚焦图像进行有效融合，提出了一种小波域中基于区域特征的自适应多聚焦图像融合方法。
To fuse different multi-focus images effectively, an adaptive fusion method of multi-focus images based on regional features in wavelet domain is proposed.
基于自适应模糊神经网络，提出一种新的特征信息融合算法。
The fuzzy neural network is analyzed. Based on the fuzzy neural network, a new attribute information fusion method is presented.
基于自适应模糊神经网络，提出一种新的特征信息融合算法。
The fuzzy neural network is analyzed. Based on the fuzzy neural network, a new attribute information fusion method is presented.
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