absrtact on fft using labview

1. ABSTRACT
TITLE: IMPLEMENTATIONOF FAST FOURIER TRANSFORMATION
USING LABVIEW
INTRODUCTION:
The Fourier transform converts a time domain representation of a signal into a frequency domain
representation. However, a digitizer samples a waveform and transforms it into discrete values.
The Fast Fourier Transform (FFT) is an optimized implementation of a DFT that takes less com -
putation to perform. Direct implementation of the DFT requires approximately n^2 complex
operations. But fft , computationally efficient algorithms can require as little as n log2(n) operati
ons.
BODY OF PROJECT:
The most commonly used FFT is the Cooley–Tukey algorithm. This is a divide and conquer
algorithm that recursively breaks down a DFT of any composite size N = N1N2 into many smaller
DFTs of sizes N1 and N2, along with O(N) multiplications by complex roots of unity traditionally
called twiddle factors . FFT properties, magnitude and phase information can be obtained
through graphical method
SOFTWARE REQUIRE: LABVIEW
LabVIEW is an integrated development environment designed specifically for engineers and
scientists building measurement and control systems. With a native graphical programming lan-
language, built-in IP for data analysis and signal processing, and an open architecture that ena-
bles integration of any hardware device and any software approach, LabVIEW is the software
you need to build the optimal solution that can meet your custom requirements and solve the
challenges at hand. LabVIEW is a flexible programming environment that can help you success
fully build your unique application, whether you are taking simple measurements or prototyping
with FPGA technology.
APPLICATIONS:
 Signal processing and image processing.
 Medical imaging.
 Numerical analysis.
 Digital filtering.

2. CONCLUSION:
The LabVIEW analysis VIs, located on the Signal Processing palette, maximize analysis
throughput in FFT-related applications. This document discusses FFT properties, how to
interpret and display FFT results, and how to manipulate FFT and power spectrum results to
extract useful frequency information.
Signature of the internal guide: Name of the students Roll No
Name: M. LAKSHMI RAVI TEJA 1.B.SUMA 13951A0494
Designation: ASSISTANT PROFESSOR 2.R.BHAVANA 13951A0458
Department: ECE 3.A.SHAMALA 14951A0410
4. KARTHIK 13951A0470