精品文档---下载后可任意编辑BP 神经网络和图像不变矩在布-加综合征类型识别中的应用讨论的开题报告【摘要】布-加综合征类型识别是医学领域中的重要问题。为解决这一问题，我们提出了一种基于 BP 神经网络和图像不变矩的布-加综合征类型识别方法。该方法首先对布-加综合征患者和健康人群的脑电图进行分析和处理，提取出关键的特征。然后利用图像不变矩将这些特征进行描述和编码，以便进一步的分类和识别。最后，利用 BP 神经网络对描述特征进行训练和识别。实验结果表明，该方法在布-加综合征类型识别中具有较高的准确率和可靠性。【关键词】BP 神经网络; 图像不变矩; 布-加综合征类型识别【Abstract】Buck-Ga Syndrome identification is an important problem in the medical field. To solve this problem, we propose a Buck-Ga Syndrome identification method based on BP neural network and image invariant moments. The method first analyzes and processes the electroencephalogram of Buck-Ga syndrome patients and healthy populations, and extracts key features. Then, using image invariant moments to describe and encode these features to further classify and identify. Finally, using the BP neural network to train the descriptive features. Experimental results show that this method has high accuracy and reliability in Buck-Ga syndrome identification.【Keywords】BP neural network; image invariant moments; Buck-Ga syndrome identification
