Chapter 5-Finite-length Discrete TransformB-11403211
发布时间:2024-11-28
发布时间:2024-11-28
Operations on Finite-Length Sequences
Circular Time-reversal of a Sequence (Section 2.3.1 ) Circular Shift of a Sequence(Section 2.3.2 and 5.7 ) Circular Convolution(Section 5.4 and 5.7 )
3. Circular Convolution
3、Circular Convolution
Example Determine the 4-point circular convolution of the two length-4 sequences: g[n]={1 2 0 1}, h[n]={2 2 1 1} as skecthed below
3、Circular Convolution
The result is a length-4 sequence yC[n]N 1 m 0 N
N h(n) yC (n) g (n) g (m)h n m
, 0 n N 1;
From the above we observe
yC (0) g (m)h mm 0
3
4
g[0]h[0] g[1]h[3] g[2]h[2] g[3]h[1] 1 2 2 1 0 1 1 2 6
3、Circular Convolution
Likewise, yC (1) g (m)h 1 mm 0
3
4
g[0]h[1] g[1]h[0] g[2]h[3] g[3]h[2] 1 2 2 2 0 1 1 1 7 yC (2) g (m)h 2 mm 0 3 4
g[0]h[2] g[1]h[1] g[2]h[0] g[3]h[3] 1 1 2 2 0 2 1 1 6
3、Circular ConvolutionyC (3) g (m)h 3 mm 0 3 4
g[0]h[3] g[1]h[2] g[2]h[1] g[3]h[0] 1 1 2 1 0 2 1 2 5
yC[n]
3、Circular Convolution
循环卷积过程图解h(0)g (0)
h(1)g (0)
h(1)
g (3)
g (1) h(3)
h(2)
g (3)
g (1) h(0)
g (2)h(2)
g (2)h(3)
(a) yc[0]
(b) yc[1]
3、Circular Convolution
The circular convolution can also be computed using a DFT-based approach The N-point circular convolution can be written in matrix form as
3、Circular Convolution
Note: 1、The element in each row of the matrix are obtained by circularly rotating the elements of the previous row to the right by one position. Such a matrix is called a circulant matrix(轮换矩阵、 循环行列式矩阵) 2、使用矩阵形式计算循环卷积前,需要通过补零把参与循 环卷积的两个输入序列扩充成相同长度,且此长度等于 DFT的点数
3、Circular Convolution
Example Now let us extend the two length-4 sequences to length 7 by appending each with three zero-valued samples, i.e.,
3、Circular Convolution
ge (n) {1, 2,0,1,0,0,0}he (n) {2, 2,1,1,0,0,0}
0 n 60 n 6
We next determine the 7-point circular convolution of ge[n] and he[n]:
yC (n) ge (m)he n mm 0
6
7
,0 n 6
Matrix method: Y y (1) y (2) H eGe y ( N 1) y (0) 1 g e (0) 2 g e (1) 0 Ge g e (2) 1 0 g e ( N 1) 0 0
he (0) he (1) H e he (2) he ( N
1)
2 he ( N 1) he ( N 2) he (1) 2 he (0) he ( N 1) he (2) 1 he (1) he (0) he (3) 1 0 0 he ( N 2) he ( N 3) he (0) 0
0 0 0 1 1 2 2 0 0 0 1 1 2 2 0 0 0 1 1 2 2 0 0 0 1 1 2 2 0 0 0 1 1 2 2 0 0 0 1 1 2 2
y (0) 2 y (1) 2 y (2) 1 y (3) 1 y (4) 0 y (5) 0 y (6) 0
0 0 0 1 1 2 1 2 2 0 0 0 1 1 2 6 2 2 0 0 0 1 0 5 1 2 2 0 0 0 1 5 1 1 2 2 0 0 0 4 0 1 1 2 2 0 0 1 0 1 0 0 1 1 2 2
3、Circular Convolution
As can be seen from the above that y[n] is precisely the sequence yL[n] obtained by a linear convolution of g[n] and h[n]yC[n]
Try to think: What is the relation between the circular convolution and the linear convolution?
3、Circular Convolution
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