# Short Article Explaining DSP Basics Without Math

If the math behind software defined radio and digital signal processing (DSP) concepts does your head in, the RSGB has a short document that explains core DSP concepts without any math. If you're just looking for an overview of what terms like sampling, nyquist, aliasing, number of bits, undersampling, digital filters and fast fourier transform mean, then this short article is a great start.

This article, based on a presentation first given at the 2017 RSGB Convention, is intended for the amateur radio exam tutors to help with teaching the new Software Defined Radio (SDR) material in Syllabus 2019. It goes slightly beyond the syllabus requirements and is designed to give a basic background into Digital Signal Processing (DSP), enabling Tutors to answer some questions that trainees may ask, and to help tutors develop their own knowledge. Links to suggested further reading are given for those who might want to know more.

**Direct PDF Link:** https://rsgb.services/public/exams/presentations/190427_DSP_without_maths_article_v1-3.pdf

Heh – isn’t “explaining DSP without math” kind of like “explaining painting without color”?

Readers beware: this is a well-intentioned document, but the examples (or interpretation of examples) showing the Nyquist limit are wrong. All of the plots in Fig 4 are perfectly well sampled below the Nyquist rate. The problem is that by using excel to interpolate between the samples, the author has created a visually false representation of what is actually going on. It is a shame, because it is easy enough to visualise the Nyquist limit and the effects of aliasing, but the explanation (“gone!”) associated with the plots is wrong.