Tutorial

Convolution: A Visual Digital Signal Processing Tutorial

Understanding convolution is central to understanding filtering, the Discrete Fourier Transform, and other important DSP operations.  In this tutorial, R. C. Kim explains convolution using a visual, intuitive, step-by-step method, and relates it to filtering and the DFT.

Reducing FFT Scalloping Loss Errors Without Multiplication

In this tutorial, Richard G. Lyons, author of the best-selling DSP book Understanding Digital Signal Processing, discusses the estimation of time-domain sinewave peak amplitudes based on fast Fourier transform (FFT) data.

Multipath Channel Model Using DSP

Multipath distortion is a common problem in many DSP-based data transmission systems.  Here, Neil Robertson shows how to model multipath channels using complex-coefficient FIR filters. 

Sum of Two Sinusoidal Functions

Many DSP systems use composite signals consisting of a sum of sinusoids of the same frequency, often a sine and cosine. In this tutorial, Richard G. Lyons, author of the best-selling DSP book Understanding Digital Signal Processing, thoroughly covers this important DSP topic by explaining and deriving formulas for the sum of two sinusoids of the same frequency.

Digital Signal Processing Articles


Expanded Table of Contents


Top-Level Table of Contents

A Little MLS (Maximum-Length Sequence) Tutorial

A Little MLS Tutorial

by Robert Bristow-Johnson


A Maximum-Length Sequence (MLS) has two different (but related) definitions:

One is the driving function applied to the input of a linear time invariant (LTI) system:

   x[n] = X*(-1)^a[n]

The other definition is simply the binary sequence, a[n] = 0 or 1, used in the exponent.

Cascaded Integrator-Comb (CIC) Filter Introduction

In the classic paper, "An Economical Class of Digital Filters for Decimation and Interpolation", Hogenauer introduced an important class of digital filters called "Cascaded Integrator-Comb", or "CIC" for short (also sometimes called "Hogenauer filters").

Here, Matthew Donadio provides a more gentle introduction to the subject of CIC filters, geared specifically to the needs of practicing DSP designers:

CIC Filter Introduction (130K, pdf)

Quadrature Signals: Complex, But Not Complicated

Understanding complex numbers and quadrature signals is essential for understanding DSP at both a theoretical and a practical level. Yet this strange, complex subject (based on the admittedly imaginary construct of the square root of negative one!) is among the hardest for DSP beginners to grasp - and is confusing at times even for advanced DSPers.

Digital Signal Processing Tutorials

Digital Signal Processing is a difficult and complex subject. Here, we offer tutorials to clear up some of the mysteries of DSP.

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