文件名称：Deep Belief Nets in C++ and CUDA C Volume 2
文件大小：5.51MB
文件格式：PDF
更新时间：2021-06-19 15:56:22
c++ cuda 语言
This book is roughly divided into four sections. Chapter 1 presents a technique for embedding class labels into a feature set in such a way that generative exemplars of the classes can be found. Chapters 2 and 3 present signal and image preprocessing techniques that provide effective inputs for deep belief nets. Special attention is given to preprocessing that produces complex-domain features. Chapter 4 discusses basic autoencoders, with emphasis on autoencoding entirely in the complex domain. This is particularly useful in many fields of signal and image processing. Chapter 5 is a reference for the DEEP program, available as a free download from my web site.