Interactive programming content

Chapter 1: Introduction to Systems and Signals

Explore different types of signals.

Explore elementary operations on signals.

Explore operations on the time variable of signals.

Decompose signals into their even and odd parts.

Chapter 2: Basic Building Blocks of Signals

Explore the complex exponential signal.

Explore the relation between the unit impulse and the unit step functions.

Chapter 3: Basic Building Blocks and Properties of Systems

Chapter 4: Representation of Linear Time Invariant Systems by Impulse Response and Convolution Operation

Explore convolution.

Explore convolution of two exponential functions.

Explore cross-correlation and auto-correlation.

A convolution (cross-correlation) example from machine learning.

Chapter 5: Representation of LTI Systems by Differential and Difference Equations

Chapter 6: Fourier Series Representation of Continuous Time Periodic Signals

Explore Fourier series representation for continuous time periodic signals.

Explore the Gibbs phenomenon.

An example on the duality of convolution and multiplication.

Explore trigonometric waveforms.

Chapter 7: Fourier Series Representation of Discrete Time Periodic Signals

Explore Fourier series representation for discrete time signals.

Chapter 8: Continuous Time Fourier Transform and Its Extension to Laplace Transform

Chapter 9: Discrete Time Fourier Transform and Its Extension to z-Transforms

An example application: removing unwanted noise from audio.

How to reconstruct a 2D image using only sine functions.

Chapter 10: Linear Time Invariant Systems as Filters

Filtering with low, band and high-pass.

Chapter 11: Continuous Time Sampling

Sampling and reconstruction of a continuous time signal.

Sampling and reconstruction with first-order hold.

Chapter 12: Discrete Time Sampling and Processing

Sampling and reconstruction of a discrete time signal.