Sectional Convolution - Discrete Fourier Transform

# Sectional Convolution - Discrete Fourier Transform Notes | Study Signals and Systems - Electronics and Communication Engineering (ECE)

## Document Description: Sectional Convolution - Discrete Fourier Transform for Electronics and Communication Engineering (ECE) 2022 is part of Signals and Systems preparation. The notes and questions for Sectional Convolution - Discrete Fourier Transform have been prepared according to the Electronics and Communication Engineering (ECE) exam syllabus. Information about Sectional Convolution - Discrete Fourier Transform covers topics like and Sectional Convolution - Discrete Fourier Transform Example, for Electronics and Communication Engineering (ECE) 2022 Exam. Find important definitions, questions, notes, meanings, examples, exercises and tests below for Sectional Convolution - Discrete Fourier Transform.

Introduction of Sectional Convolution - Discrete Fourier Transform in English is available as part of our Signals and Systems for Electronics and Communication Engineering (ECE) & Sectional Convolution - Discrete Fourier Transform in Hindi for Signals and Systems course. Download more important topics related with notes, lectures and mock test series for Electronics and Communication Engineering (ECE) Exam by signing up for free. Electronics and Communication Engineering (ECE): Sectional Convolution - Discrete Fourier Transform Notes | Study Signals and Systems - Electronics and Communication Engineering (ECE)
 1 Crore+ students have signed up on EduRev. Have you?

Suppose, the input sequence x(n) of long duration is to be processed with a system having finite duration impulse response by convolving the two sequences. Since, the linear filtering performed via DFT involves operation on a fixed size data block, the input sequence is divided into different fixed size data block before processing.

The successive blocks are then processed one at a time and the results are combined to produce the net result.

As the convolution is performed by dividing the long input sequence into different fixed size sections, it is called sectioned convolution. A long input sequence is segmented to fixed size blocks, prior to FIR filter processing.

Two methods are used to evaluate the discrete convolution −

• Overlap-save method

Overlap Save Method

Overlap–save is the traditional name for an efficient way to evaluate the discrete convolution between a very long signal x(n) and a finite impulse response (FIR) filter h(n). Given below are the steps of Overlap save method −

Let the length of input data block = N = L+M-1. Therefore, DFT and IDFT length = N. Each data block carries M-1 data points of previous block followed by L new data points to form a data sequence of length N = L+M-1.

• First, N-point DFT is computed for each data block.

• By appending (L-1) zeros, the impulse response of FIR filter is increased in length and N point DFT is calculated and stored.

• Multiplication of two N-point DFTs H(k) and Xm(k) : Y′m(k) = H(k).Xm(k), where K=0,1,2,…N-1

• Then, IDFT[Y′m((k)] = y′((n) = [y′m(0), y′m(1), y′m(2),.......y′m(M-1), y′m(M),.......y′m(N-1)]

(here, N-1 = L+M-2)

• First M-1 points are corrupted due to aliasing and hence, they are discarded because the data record is of length N.

• The last L points are exactly same as a result of convolution, so

y′m (n) = ym(n) where n = M, M+1,….N-1

• To avoid aliasing, the last M-1 elements of each data record are saved and these points carry forward to the subsequent record and become 1st M-1 elements.

• Result of IDFT, where first M-1 Points are avoided, to nullify aliasing and remaining L points constitute desired result as that of a linear convolution

Given below are the steps to find out the discrete convolution using Overlap method −

Let the input data block size be L. Therefore, the size of DFT and IDFT: N = L+M-1

• Each data block is appended with M-1 zeros to the last.

• Compute N-point DFT.

• Two N-point DFTs are multiplied: Ym(k) = H(k).Xm(k), where k = 0,,1,2,….,N-1

• IDFT [Ym(k)] produces blocks of length N which are not affected by aliasing as the size of DFT is N = L+M-1 and increased lengths of the sequences to N-points by appending M-1 zeros to each block.

• Last M-1 points of each block must be overlapped and added to first M-1 points of the succeeding block.

(reason: Each data block terminates with M-1 zeros)

Hence, this method is known Overlap-add method. Thus, we get −

y(n) = {y1(0), y1(1), y1(2), ... .., y1(L-1), y1(L)+y2(0), y1(L+1)+y2(1), ... ... .., y1(N-1)+y2(M-1),y2(M), ... ... ... ... ... }

The document Sectional Convolution - Discrete Fourier Transform Notes | Study Signals and Systems - Electronics and Communication Engineering (ECE) is a part of the Electronics and Communication Engineering (ECE) Course Signals and Systems.
All you need of Electronics and Communication Engineering (ECE) at this link: Electronics and Communication Engineering (ECE)

## Signals and Systems

32 videos|76 docs|64 tests
 Use Code STAYHOME200 and get INR 200 additional OFF

## Signals and Systems

32 videos|76 docs|64 tests

### Top Courses for Electronics and Communication Engineering (ECE)

Track your progress, build streaks, highlight & save important lessons and more!

,

,

,

,

,

,

,

,

,

,

,

,

,

,

,

,

,

,

,

,

,

;