This curriculum is designed to expose you to a broad range of signal-processing topics focussing on signal-processing applications.
Foundations
- Signals Everywhere
- Ever-Present Noise
- Models, Math, and Real-World Signals
- Four Signal-Processing Themes
- Building Signals with Blocks: Basis Expansions
- Signals: The Basics
- Sinusoidal Signals
- Sinusoidal Signals Examples
- Complex Sinusoids
- Exponential, Step, and Impulse Signals
- Introduction to Linear, Time-Invariant Systems
- Introduction to Difference Equation System Descriptions
- Impulse Response Descriptions for LTI Systems
- Frequency Response Descriptions for LTI Systems
- Introduction to the System Function and System Poles and Zeros
- The Four Fourier Representations
LTI Systems and Fourier Transforms
- Impulse Response and LTI Systems - Part II
- The Fourier Transform:Linking Time and Frequency Domains
- Properties of the Fourier Transform
- The Discrete-Time Fourier Transform
- Discrete-Time Fourier Transform Properties
Sampling and Reconstruction
- Introduction to Sampling and Reconstruction
- Aliasing and the Sampling Theorem Simplified
- Practical Sampling: Anti-Aliasing Filters
The DFT and Applications
- Discrete Fourier Transform: Sampling the Discrete-Time Fourier Transform
- Important Discrete Fourier Transform Properties
- Fast Fourier Transform (FFT) Algorithm
- Introduction to Circular Convolution and Filtering with the DFT
- The Discrete Fourier Transform Approximation to the Fourier Transform
- The Effect of Windowing on the Discrete Fourier Transform Approximation to the Fourier Transform
- Windows and the Discrete-Time Fourier Transform: Trading Resolution for Dynamic Range
- An Example of Approximating the Fourier Transform with the Discrete Fourier Transform
- The Short-Time Fourier Transform and the Spectrogram
The 
-Transform
- Introduction to the z-Transform
- Poles and Zeros of the z-Transform
- Frequency Response Magnitude and Poles and Zeros
Intro to Filter Design
- Introduction to Frequency Selective Filtering
- Characterizing Filter Phase Response
- Zero-Phase Filtering
- Overview of FIR and IIR Filters
IIR Filter Design
- IIR Filter Design Procedure
- Analog Filters Used for IIR Filter Design
- IIR Filter Examples Designed Using MATLAB
- Poor IIR Filter Designs: Don't Make These Mistakes
FIR Filter Design
- Introduction to FIR Filter Design
- Linear Phase FIR Filters
- Parks-McClellan FIR Filter Design
- Examples of Parks-McClellan FIR Filter Design
Random Signal Characterization
- Introduction to Random Signal Representations
- Multivariable Random Signal Characterization
- Random Processes and Stationarity
- The Power Spectral Density
- Cross Spectra and Coherence
- LTI System Models for Random Signals
- Autoregressive Models: The Yule-Walker Equations
Basis Representation of Signals
- Introduction to Signal Representation Using Bases
- Introduction to Wavelets
- Multiresolution Analysis and the Scaling Function
- Multiresolution Analysis and the Wavelet Decomposition
- The Discrete Wavelet Transform
- Wavelet Selection
- Principal Component Analysis
Estimation of Signal Characteristics
- Introduction to Estimation Theory
- Parametric vs. Nonparametric Spectrum Estimation
- The Periodogram
- The Averaged Periodogram: Welch's Method
- Power Spectrum Estimation Examples: Welch's Method
- Estimation of Coherence and Cross Spectra
- Parameter Estimation Criteria
- Maximum Likelihood Estimation Examples
