1 2 3 4 5 6 7 8 9
10
11
12
13
14
15
16
17
18
9.1 • THE Z..TRANSFORM 345
Solution Let both Xn =land Yn = 1 be the unit step sequence, and X(z) =
2
Y(z) = (z:i)· Then W(z) = X(z)Y(z) = (•:l)'' so that Wn is given by the
convolution
n n
Wn = Xn * Yn = L XiYn-i = L 1 = n + 1.
i=O i=O
9.1.5 Application to Signal Processing
Digital signal processing often involves the design of finite impulse response (FIR)
filters. A simple 3-point FIR filter can be described as
y [n] = x[n] +a. x{n - l] + b x[n - 2]. (9-4)
Here, we choose real coefficients a and b so that the homogeneous difference
equation
x[n] +a. x[n - l] + b x[n - 2] = 0 (9-5)
has solutions x[n] = cos(w7rn) and x[n] = sin(wirn). That is, if the linear com-
bination x(n] = c 1 cos(w7rn) + c2sin(wirn) is input on the right side of the FIR
filter equation, the output y[n] on the left side of the equation will be zero.
Sequence z-transform
Definition Xn = x{n] X(z) = I:::"=oXnZ- n
Addition Xn+Yn X(z) + Y (z)
Constant multiple CXn cX(z)
Linearity CXn + dy,, cX(z) + dY(z)
Delayed unit step u [n-m]
z t-m
z-1
Time delay 1 tap Xn-1u[n - 1] ~X(z)
Time delayed shift Xn-mu[n-m] z -mx(z)
Forward 1 tap Xn+J z (X(z) - xo)
Forward 2 taps Xn+2 z^2 (X(z) - xo -x1z-^1 )
Time forward Xn+m Z m(x() Z - L:m-1 i=O X;Z -i)
Complex translation e""Xn X (ze- ")
Frequency scale b"xn x (~)
Differentiation nxn - zX '(z)
Integration ;Xn l -f Xiz) dz
Integration shift n+n:;l Xn -z- m J ;.~~ dz
Discrete-time convolution Xn * Yn = L:7=o X;Yn-i X(z)Y(z)
Convolution with Yn = 1 L:~;QXi z:J X(z)
Initial time XO limz-oo X(z)
Final value lilll.n-oo Xn lim,._ 1 (z - l)X(z)
Table 9.2 Some properties of the z-tra.nsform.