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

by Timothy Masters

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 several algorithms for preprocessing time series and image data. These algorithms focus on the creation of complex-domain predictors that are suitable for...

• Format: Paperback
• Language: English
• ISBN: 1484236459
• ISBN13: 9781484236451
• Release Date: June 2018
• Publisher: Apress
• Length: 258 Pages
• Weight: 1.05 lbs.
• Dimensions: 0.6" x 7.0" x 10.0"