Deep Belief Nets in C++ and CUDA C: Volume 2 Autoencoding in the Complex Domain /

• Main Author: Masters, Timothy (Author, http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berkeley, CA : Apress : Imprint: Apress, 2018.
• Edition: 1st ed. 2018.
• Subjects: Artificial intelligence.; Programming languages (Electronic computers).; Big data.; Artificial Intelligence.; Programming Languages, Compilers, Interpreters.; Big Data.; Big Data/Analytics.

Discover the essential building blocks of a common and powerful form of deep belief net: the autoencoder. You'll take this topic beyond current usage by extending it to the complex domain for signal and image processing applications. Deep Belief Nets in C++ and CUDA C: Volume 2 also covers seve...

Table of Contents:

• 0. Introduction
• 1. Embedded Class Labels
• 2. Signal Preprocessing
• 3. Image Preprocessing
• 4. Autoencoding
• 5. Deep Operating Manual.