CHAP. 6 1
Reading USS Code 128 In NoneUsing Barcode Control SDK for Software Control to generate, create, read, scan barcode image in Software applications.
Code 128 Code Set A Printer In NoneUsing Barcode encoder for Software Control to generate, create Code 128A image in Software applications.
THE DFT
Decoding Code 128B In NoneUsing Barcode decoder for Software Control to read, scan read, scan image in Software applications.
Painting ANSI/AIM Code 128 In C#.NETUsing Barcode maker for VS .NET Control to generate, create Code128 image in VS .NET applications.
Periodic Convolution
Code 128 Code Set B Drawer In .NET FrameworkUsing Barcode drawer for ASP.NET Control to generate, create Code 128A image in ASP.NET applications.
Code 128 Printer In Visual Studio .NETUsing Barcode creation for VS .NET Control to generate, create Code 128 Code Set B image in VS .NET applications.
1f h(n) and i ( n ) are periodic with a period N with DFS coefficients &(k) and g ( k ) , respectively, the sequence with DFS coefficients F(k)= 4 (k)f (k)
Code128 Generation In Visual Basic .NETUsing Barcode creation for Visual Studio .NET Control to generate, create Code128 image in VS .NET applications.
Bar Code Drawer In NoneUsing Barcode creator for Software Control to generate, create bar code image in Software applications.
is formed by periodically convolving h(n) with R(n) as follows:
Data Matrix Encoder In NoneUsing Barcode maker for Software Control to generate, create ECC200 image in Software applications.
EAN13 Encoder In NoneUsing Barcode encoder for Software Control to generate, create EAN13 image in Software applications.
Notationally, the periodic convolution of two sequences is written as
Code 39 Generation In NoneUsing Barcode creation for Software Control to generate, create Code 3 of 9 image in Software applications.
Code 128C Generation In NoneUsing Barcode encoder for Software Control to generate, create Code 128C image in Software applications.
The only difference between periodic and linear convolution is that, with periodic convolution, the sum is only evaluated over a single period, whereas with linear convolution the sum is taken over all values of k.
USD - 8 Generation In NoneUsing Barcode encoder for Software Control to generate, create Code11 image in Software applications.
UPCA Printer In NoneUsing Barcode encoder for Office Word Control to generate, create UPCA image in Microsoft Word applications.
EXAMPLE 6.2.2
DataMatrix Recognizer In JavaUsing Barcode reader for Java Control to read, scan read, scan image in Java applications.
Barcode Drawer In JavaUsing Barcode drawer for BIRT Control to generate, create bar code image in Eclipse BIRT applications.
Let us periodically convolve the two sequences pictured below that have a period N = 6.
Drawing UPC Symbol In NoneUsing Barcode encoder for Font Control to generate, create GTIN - 12 image in Font applications.
Create Code 39 In Visual Studio .NETUsing Barcode encoder for ASP.NET Control to generate, create Code 39 image in ASP.NET applications.
The periodic convolution of two sequences may be performed graphically, analytically, or using the DFS. In this problem, we will use the graphical approach. We begin by plotting P(n - k ) versus k . This sequence, for n = 0. is illustrated below.
Generate UPC-A Supplement 5 In Objective-CUsing Barcode creator for iPad Control to generate, create UPC-A Supplement 2 image in iPad applications.
Code 128B Maker In NoneUsing Barcode maker for Office Excel Control to generate, create Code 128 Code Set B image in Office Excel applications.
The value of J(0)is then Found by summing the product i ( k ) f ( - k ) from X- = 0 to k = 5. The result is j ( 0 ) = 1 . Next, f ( - k ) is shifted to the right by one and multiplied by h ( k ) . Because the only two nonzero values of P(1 - k ) are at k = 4.5. the product h"(k)f(l - k ) is equal to zero, and J ( I ) = 0 . This process is continued until we have one period of J ( n ) . The result is illustrated below.
T H E DFT
[CHAP. 6
6.3 DISCRETE FOURIER TRANSFORM
The DFT is an important decomposition for sequences that are finite in length. Whereas the DTFT is a mapping from a sequence to a function of a continuous variable, w ,
the DFT is a mapping from a sequence, x ( n ) , to another sequence, X ( k ) ,
The DFT may be easily developed from the discrete Fourier series representation for periodic sequences. Let
x ( n ) be a finite-length sequence of length N that is equal to zero outside the interval [0, N - I]. A periodic sequence i ( n ) may be formed from x ( n ) as follows:
This periodic extension may be expressed as follows:
i ( n ) = x ( n mod N) r ~ ( ( n ) ) ~
where ( n mod N ) and ((n))N are taken to mean "n modulo N ." That is to say, if n is written in the form n = kN + I where 0 5 I < N ,
( n mod N) = ( ( n ) ) = I ~
For example, (( 13))8 = 5 and ( ( - 6 ) ) x = 2. A periodic sequence may be expanded using the DFS as in Eq. ( 6 . 1 ) . Because x ( n ) = 2 ( n ) for n = 0, 1, . . . , N - 1 , x ( n ) may similarly be expanded as follows:
Because the DFS coefficients are periodic, if we let X ( k ) be one period of i ( k ) and replace%(k) in the sum with X ( k ) , then we have
The sequence X ( k ) is called the N-point DFT of x ( n ) . These coefficients are related to x ( n ) as follows:
Equations ( 6 . 4 ) and ( 6 . 5 ) form a DFT pair, and we write
This expansion is valid for complex-valued as well as real-valued sequences. Comparing the definition of the DFT of x ( n ) to the DTFT, it follows that the DFT coefficients are samples of the DTFT:
CHAP. 61
THE DFT
Alternatively, the DFT coefficients correspond to N samples of X ( z ) that are taken at N equally spaced points around the unit circle:
X ( k ) = X(z)lz=exp(j nklNJ 6.4 DFT PROPERTIES
In this section, we list some of the properties of the DFT. Because each sequence is assumed to be finite in length, some care must be exercised in manipulating DFTs.