Harris C M
Department of Ophthalmology, Great Ormond Street Hospital for Children NHS Trust, Institute of Child Health, University College London, UK.
J Neurosci Methods. 1998 Aug 31;83(1):15-34. doi: 10.1016/s0165-0270(98)00080-6.
With modern computing technology the digital implementation of the Fourier transform is widely available, mostly in the form of the fast Fourier transform (FFT). Although the FFT has become almost synonymous with the Fourier transform, it is a fast numerical technique for computing the discrete Fourier transform (DFT) of a finite sequence of sampled data. The DFT is not directly equivalent to the continuous Fourier transform of the underlying biological signal, which becomes important when analyzing biological transients. Although this distinction is well known by some, for many it leads to confusion in how to interpret the FFT of biological data, and in how to precondition data so as to yield a more accurate Fourier transform using the FFT. We review here the fundamentals of Fourier analysis with emphasis on the analysis of transient signals. As an example of a transient, we consider the human saccade to illustrate the pitfalls and advantages of various Fourier analyses.
借助现代计算技术，傅里叶变换的数字实现方式广泛可得，大多以快速傅里叶变换（FFT）的形式存在。尽管FFT几乎已成为傅里叶变换的代名词，但它是一种用于计算有限采样数据序列离散傅里叶变换（DFT）的快速数值技术。DFT与基础生物信号的连续傅里叶变换并不直接等同，这在分析生物瞬变时变得很重要。尽管有些人很清楚这种区别，但对许多人来说，这会导致在如何解释生物数据的FFT以及如何预处理数据以便使用FFT得到更准确的傅里叶变换方面产生困惑。我们在此回顾傅里叶分析的基本原理，重点是瞬态信号的分析。作为一个瞬态的例子，我们考虑人类的眼跳来阐明各种傅里叶分析的陷阱和优势。
