Book Image

C++17 STL Cookbook

By : Jacek Galowicz
Book Image

C++17 STL Cookbook

By: Jacek Galowicz

Overview of this book

C++ has come a long way and is in use in every area of the industry. Fast, efficient, and flexible, it is used to solve many problems. The upcoming version of C++ will see programmers change the way they code. If you want to grasp the practical usefulness of the C++17 STL in order to write smarter, fully portable code, then this book is for you. Beginning with new language features, this book will help you understand the language’s mechanics and library features, and offers insight into how they work. Unlike other books, ours takes an implementation-specific, problem-solution approach that will help you quickly overcome hurdles. You will learn the core STL concepts, such as containers, algorithms, utility classes, lambda expressions, iterators, and more, while working on practical real-world recipes. These recipes will help you get the most from the STL and show you how to program in a better way. By the end of the book, you will be up to date with the latest C++17 features and save time and effort while solving tasks elegantly using the STL.
Table of Contents (18 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Implementing the Fourier transform formula with STL numeric algorithms


The Fourier transformation is a very important and famous formula in signal processing. It was invented nearly 200 years ago, but with computers, the number of use cases for it really skyrocketed. It is used in audio/image/video compression, audio filters, medical imaging devices, cell phone apps that identify music tracks while listening to them on the fly, and so on.

Because of the vastness of general numeric application scenarios (not only because of the Fourier transformation of course), the STL also tries to be useful in the context of numeric computation. The Fourier transformation is only one example among them but a tricky one too. The formula itself looks like the following:

The transformation it describes is basically a sum. Each element of the sum is the multiplication of a data point of the input signal vector, and the expression exp(-2 * i * ...). The maths behind this is a bit scary for everyone who does not...