The discrete Fourier transform is one of the most important computational tools in signal processing. This lesson briefly introduces you to some of the applications for the discrete Fourier transform, its definition, and develops the relationship between the discrete Fourier transform and the discrete-time Fourier transform. An understanding of this relationship is essential to proper use […]

# Free

## Signals Everywhere

This lesson introduces you to the concepts of “signals” and “signal processing” with computers. You will develop an appreciation for the incredible breadth of signal processing applications. You will also gain valuable perspective of key historical factors that have shaped the field. This information lays the foundation for you to be able to apply signal-processing […]

## 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 […]

## Linear Phase FIR Filters

A significant benefit of FIR filters is that they can be guaranteed to have linear phase and not to introduce phase distortion. In this lesson you will learn the constraints place on the filter coefficients and frequency response when we require linear phase. For example, you will learn why certain orders cannot be used to […]