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Description: 采用神经网络实现手写识别的一种方法，建立Bp神经网络，采用快速训练方法，可快速完成一类相关手写字体的模式识别，识别率较高，当字体变化较大识别率降低时，可重新训练具有较强的适应性。实验证实本方法较好实现了手写字符识别，但也存在识别速度较慢，有时训练不收敛等缺点-Handwriting recognition using neural network is a way to establish Bp neural network, using fast training methods, and can be related to the completion of a class of handwriting pattern recognition, recognition rate higher recognition rate when the font changed greatly reduced, they can re- Training has strong adaptability. Experiments confirmed that this method achieved a better handwritten character recognition, but there are also identified slow, and sometimes non-convergence of the training deficiencies
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Size: 105472 |
Author: caoliang |
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Description: 此例可采用BP神经网络算法用于设备故障类型的模式识别程序。 本次为变压器故障（均为低压测故障）类型的识别。-This example can be used BP neural network algorithm for pattern recognition procedures for equipment fault type. The identification of the type of transformer fault (both low pressure fault detection).
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Size: 7168 |
Author: 蔡丽桑 |
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Description: BP神经网络识别手写字符验证码，包括10721张字母、数字样本-BP neural network handwritten character recognition codes, including 10,721 letters, numbers, samples
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Size: 3356672 |
Author: 武峥 |
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