The document discusses the Fast Fourier Transform (FFT), highlighting its efficiency in reducing computation time and improving performance compared to the Discrete Fourier Transform. It explains the two main algorithms for FFT: Decimation in Time (DIT) and Decimation in Frequency (DIF), and outlines the steps to execute FFT. Additionally, FFT is noted for its applications in analyzing large datasets, such as communication signals and electrocardiograms.

1. FAST FOURIER TRANSFORM
By
Mrs.R.Chitra,
Assistant Professor(SS),
Department of ECE,
School of Engineering,
Avinashilingam Institute for Home Science and Higher
Education for Women, Coimbatore

2. FAST FOURIER TRANSFORM
• Fast Fourier transform reduces the time of
computation and also number of
computations to be performed.
• It also improves the performance when
compared to discrete Fourier transform.
• FFT can also be known as DIVIDE AND
CONQUER ALGORITHM.

3. There are basically two classes of FFT
algorithms,they are
 Decimation in time(DIT)
 Decimation in frequency(DIF)

4. STEPS TO EXECUTE FFT
• Divide the data set into two or more sub data
sets.
• Solve each sub data set recursively and
terminate the recursion when the data set
length is small.
• Obtain the solution to the original data swt by
combining the solution to the each sub data
sets.

5. DECIMATION IN TIME ALGORITHM
This algorithm is also known as Radix-2 DIT FFT.

19. DECIMATION IN FREQUENCY
ALGORITHM

28. APPLICATIONS OF FOURIER
TRANSFORM
• It can be used for analysis of large data
sets.For example,communication signals over
a period of time (information from the
satellite),electrocardiogram from the human
body.