Sampling and reconstruction are two of the most essential and widely used operations in signal-processing systems. In this lesson you will be introduced to the roles of sampling and reconstruction in signal processing and the questions that will be addressed in subsequent lessons. All signals in the physical world, e.g., sound or light intensity, have […]

## Ever-Present Noise

The most dominant factors in the field of signal processing are noise and its sister, interference. Noise and interference is the motivating root of almost all signal-processing methods. This lesson introduces you to the notions of noise and interference and explains why they are always present. You will gain an understanding for the context for […]

## Models, Math, and Real-World Signals

In this third lesson on fundamental signal processing concepts you will learn about the role of mathematical models in signal processing. Models are used to describe characteristics of signals and or noise that are relevant to the information of interest in the signal. Mathematical models underlie all algorithms in signal processing, including separation of signals […]

## Four Signal-Processing Themes

This lesson introduces you to four common signal-processing problems that transcend many application areas. You will gain a general perspective of the overarching goals of the signal processing without the complications of specific applications and methods. This high level introduction will help you maintain the proper perspective and context when you later immerse yourself in […]

## Jupyter Notebook: Explore FIR Filtering

Filters are used to change the character of signals in a desired manner. This activity will give you hands-on experience with simple filters and begin developing your intuition. You will see the effect of the filter in the graph and hear the effect via audio. The design of filters for specific purposes is an extensive […]

## Square Wave Fourier Series and the Sinc Function

The square wave Fourier series provides fundamental insight into the nature of Fourier series expansions. You will learn the relationship between the width or duty cycle of a square wave and the concentration of the Fourier series coefficients. You will also be introduced to the sinc function, a function that has widespread significance in all […]