FFT算法研究及基2FFT算法的C语言实现.doc

毕 业 设 计 [论 文] 题 目： 学 院： 电气与信息工程学院 专 业： 姓 名： 学 号： 指导老师： 完成时间： 201年06月01日 摘 要 离散傅立叶变换（DFT）常常用于计算信号处理。DFT算法可以得到信号的频域特性，因为该算法在计算上是密集的，长时间的使用时，计算机不能实时进行信号处理。所以DFT被发现之后的相当长时间内是没被应用到实际的项目。到了二十世纪六十年代中期一种新的计算方法被研究者发现出来，它就是FFT。FFT并不是一种新的获取频域特征的方式，而是离散傅里叶变换的一种快速实现算法。 数字信号处理在当今科技发展中发展很迅速，不但是在传统的通信领域，其他方面也经常用到。利用快速傅里叶变换，实现了信号频域的变换处理。对于信号的处理，往往会和数学中的算法联系到一起。如果处理得当，将会对气象，地理信息等的发展，起到举足轻重的作用，同时对世界其他领域的发展有很大的促进作用。 关键词: FFT算法，C语言，编译实现  Abstract Discrete Fourier Transform (DFT) is often used to calculate the signal processing to obtain frequency domain signals. DFT algorithm can get the frequency domain characteristics of the signal, because the algorithm is computationally intensive, long-time use, the computer is not conducive to real-time signal processing. So DFT since it was discovered in a relatively long period of time is not to be applied to the actual projects until a new fast discrete Fourier calculation method --FFT is found in discrete Fourier transform was able to actually project has been widely used. FFT is not a new way to get the frequency domain, but the discrete Fourier transform of a fast algorithm. Fast Fourier Transform (FFT) is a digital signal processing important tool that the time domain signal into a frequency-domain signal processing. matched filtering has important applications. FFT is a discrete Fourier transform (DFT) is a fast algorithm, it can be a signal from the time domain to the frequency domain. Some signals in the time domain is not easy to observe the characteristics of what is, but then if you change the signal from the time domain to the frequency domain, it is easy to see out of. This design is required to be familiar with the basic principles of FFT algorithm, based on the preparation of