分析比较了各主要模式识别方法的特点。对板形模式识别方法的发展趋势进行了讨论。
The characteristics of various chief pattern recognition methods are analyzed and compared, and the trend of development of the method is symposiumed.
为制定合理的控制策略，须对实测板形进行模式识别，并以约定的参数定量地提供给下一控制环节。
The real shape must be recognized to establish rational control strategy and the recognition results must be quantificationally provided to the next control link with promissory parameters.
本文提出了基于模糊距离的R BF网络板形缺陷模式识别法。
In this paper, we put forward using RBF network to flatness pattern recognition.
为了提高带材板形识别的精度，应用神经网络和最优化方法，构建了一种新的板形信号模式识别方法。
In order to improve the pattern recognition precision, using the neural network recognition and optimal method, a new pattern recognition method of shape signal was established.
为了提高带材板形识别的精度，应用神经网络和最优化方法，构建了一种新的板形信号模式识别方法。
In order to improve the pattern recognition precision, using the neural network recognition and optimal method, a new pattern recognition method of shape signal was established.
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