Principal Component Analysis Networks and Algorithms is popular PDF and ePub book, written by Xiangyu Kong in 2017-01-09, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Principal Component Analysis Networks and Algorithms can be Read Online from any device for your convenience.
Principal Component Analysis Networks and Algorithms Book PDF Summary
This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.
Detail Book of Principal Component Analysis Networks and Algorithms PDF
- Author : Xiangyu Kong
- Release : 09 January 2017
- Publisher : Springer
- ISBN : 9789811029158
- Genre : Technology & Engineering
- Total Page : 339 pages
- Language : English
- PDF File Size : 20,5 Mb
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