**MATLAB/Octave
Scripts to Accompany**

“**Signals
& Systems: Theory and Applications”**

The MATLAB/Octave scripts below were written to mimic the Labview simulation modules that were developed to accompany the textbook “Signals & Systems: Theory and Applications” by Fawwaz Ulaby and Andrew Yagle. This text and the corresponding Labview modules are available for free download from ss2.eecs.umich.edu. I plan to use the textbook and found the Labview modules to be very educational. We primarily use MATLAB/Octave as a simulation tool, hence the effort to mimic the Labview modules. Modules for Chapter 10 are in development. Modules have been tested under Octave 4.4.0 and MATLAB R2018a.

Tony Richardson

University of Evansville

richardson.tony@gmail.com

**ZIP Archive
Containing All Files**

**Input Files
(Required by the Chapter 6, 8, 9, and 10 scripts)**

trumpet.csv, twotrumpetsGA.csv, twotrumpetsAB.csv, victorstone.csv

**Chapter 2: Linear
Time-Invariant Systems**

2.1: Convolution of Exponential Functions

2.2: Automobile Suspension Response

**Chapter 4:
Applications of the Laplace Transform**

4.2: Inverted Pendulum Response

**Chapter 6:
Applications of the Fourier Transform**

6.1: Notch Filter to Remove Sinusoid from a Trumpet Signal

6.2: Comb Filter to Separate two Trumpet Signals

6.3: Filtering a Noisy Trumpet Signal

**Chapter 8:
Applications of Discrete-Time Signals and Systems**

8.1: Discrete-Time Frequency Response from Poles and Zeros

8.2: Discrete-Time Notch Filter to Eliminate One of Two Sinusoids

8.3: Discrete-Time Notch Filter to Eliminate Sinusoid from Trumpet Signal

8.4: Discrete-Time Comb Filter to Eliminate Periodic Signal from Sinusoid

8.5: Discrete-Time Comb Filter to Separate Two Trumpet Signals

8.6: Dereverberation of a Simple Signal

8.7: Denoising a Trumpet Signal by Thresholding

8.8: Separating Two Trumpet Signals Using the DFT

8.9: Computing Spectra of DT Periodic Signals Using the DFT

8.10: Computing CT Fourier Transforms Using the DFT

mod08_10a.m, mod08_10b.m, mod08_10c.m

**Chapter 9: Filter
Design, Multirate, and Correlation**

9.1: Discrete-Time Lowpass Filter Design Using Windowing

9.2: Spectrogram of Tonal Version of "The Victors"

9.3: Spectrogram of a Chirp Signal

9.4: Use of Autocorrelation to Estimate Period

9.5: Use of Cross-correlation to Estimate Time Delay

**Chapter 10: Image
Processing, Wavelets, and Compressed Sensing**

10.1: Effect of Lowpass Filtering an Image