Transfer Functions
Zeroes and Poles
Suppose that we represent a transfer function as:
To find the zeroes of a transfer function, solve for such that
Similarly, to find the poles of a transfer function, solve for such that
Solving for roots in polynomials may result in complex and/or repeated roots.
Factoring roots with NumPy
import numpy as np
coeffs = [1, -0.25, -1, -1.2]
roots = np.roots(coeffs)
print(roots)
Plotting roots with matplotlib
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(5,5))
# draw unit circle
theta = np.linspace(0, 2*np.pi, 400)
ax.plot(np.cos(theta), np.sin(theta))
# plot roots
ax.scatter(roots.real, roots.imag, marker='o')
# set up axes
ax.axhline(0)
ax.axvline(0)
ax.set_aspect('equal', adjustable='box')
ax.set_xlabel('Re')
ax.set_ylabel('Im')
plt.tight_layout()
plt.show()
First-Difference Filters
Impulse Function:
Transfer Function:
Cascaded First-Difference Filters Example
Find the transfer function for a third-order cascade of first-difference filters.
The transfer function for a single first-difference filter is . To cascade this filter, we multiply it by itself. Thus,
Alternatively, if we represent the first-difference filter transfer function as , then:
This fraction form makes it easier to find the zeroes and pole of the filter.
Inverse Z-transforms
Properties
Linearity
If and , then:
Time-Shifting
Transforms to Know
Polynomial
Proof
Recall that the equation for Z-transforms is given by:
Then, if ,
Polynomial Example
Find the impulse function for .
Using :
Geometric Series
Geometric Series Example
Find the impulse function for the system .
We start off by putting the equation in standard form:Then, using Z-transform’s time-shifting property , the equation can be represented in the -domain:
We can then organize this equation to solve for the transfer function:
This can be rewritten using partial fraction decomposition:
Partial Fraction Decomposition Review!
Multiply both sides with to get:
When , gets cancelled out and we can solve for :
Similarly, when , we can solve for B:
We can plug these values back into the above equation.
Finally, using the transform ,