基于人工神经网络的多源信息融合技术研究

Research of Multi-source Information Data Fusion Technology Based on Artificial Neural Network

随着科技的飞速发展，多媒体、各种信息源获得的图像数据信息量大、范围广、冗余大，面对如此庞大的数据，要想更合理、高效地利用，必须对这些海量数据进行融合，所以多源信息融合技术成为各个领域的研究热点。人工神经网络由大量互联的处理单元连接而成，跟人的认知处理过程及其相似，具有很强的自学习能力，对不确定的各事物进行关联，以获得对同一事物或目标的更客观、更本质认识的综合信息。基于人工神经网络的多源信息融合技术，结合双方的特点与优势，经过实验证明，融合后的图像效果良好。

With the rapid development of science and technology, obtained by multimedia, a variety of information sources, the amount of image data is big, extensive, and redundant. In face of so much data, these massive data must be integrated for a more rational and efficient use. So the integration of multi-source information technology become a hotspot of the various fields of research. Artificial Neural Net- works is made of a large number of Intemet connections from the processing unit, similar of people＇s cognitive processing, with strong self-learning ability of the uncertainty for the relation of all things, accessed to more objective and more comprehensive understanding of the nature of the information for the same things or more goals. Multi-source information fusion technology based on ANN, combining the characteristics and advantages of the two sides, the experiment proved that the integrated image is vivid.