Cartwright Hugh M
Department of Chemistry, University of Oxford, Physical and Theoretical Chemistry Laboratory, UK.
Methods Mol Biol. 2008;458:1-13. doi: 10.1007/978-1-60327-101-1_1.
Once regarded as an eccentric and unpromising algorithm for the analysis of scientific data, the neural network has been developed in the last decade into a powerful computational tool. Its use now spans all areas of science, from the physical sciences and engineering to the life sciences and allied subjects. Applications range from the assessment of epidemiological data or the deconvolution of spectra to highly practical applications, such as the electronic nose. This introductory chapter considers briefly the growth in the use of neural networks and provides some general background in preparation for the more detailed chapters that follow.
神经网络曾被视为一种用于分析科学数据的古怪且前景不佳的算法,但在过去十年中已发展成为一种强大的计算工具。如今,它的应用涵盖了科学的所有领域,从物理科学、工程学到生命科学及相关学科。其应用范围从流行病学数据评估、光谱去卷积到诸如电子鼻等高度实用的应用。本章引言简要回顾了神经网络使用的增长情况,并提供了一些一般背景知识,为后续更详细的章节做准备。