Deep Belief Nets in C++ and CUDA C: Volume 2

Autoencoding in the Complex Domain

Paperback Engels 2018 9781484236451
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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 input to a complex-domain autoencoder. Finally, you’ll learn a method for embedding class information in the input layer of a restricted Boltzmann machine. This facilitates generative display of samples from individual classes rather than the entire data distribution. The ability to see the features that the model has learned for each class separately can be invaluable. 
At each step this book provides you with intuitive motivation, a summary of the most important equations relevant to the topic, and highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. 

What You'll LearnCode for deep learning, neural networks, and AI using C++ and CUDA C
Carry out signal preprocessing using simple transformations, Fourier transforms, Morlet wavelets, and more
Use the Fourier Transform for image preprocessing
Implement autoencoding via activation in the complex domain
Work with algorithms for CUDA gradient computation
Use the DEEP operating manual

Who This Book Is For
Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.

Specificaties

ISBN13:9781484236451
Taal:Engels
Bindwijze:paperback
Uitgever:Apress

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Inhoudsopgave

<p>0. Introduction.- 1. Embedded Class Labels.- 2. Signal Preprocessing.- 3. Image Preprocessing.- 4. Autoencoding.- 5. Deep Operating Manual.</p><br>

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        Deep Belief Nets in C++ and CUDA C: Volume 2