Mohlo by se vám také líbit

Více informací o knize Principal Component Analysis Networks and Algorithms

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 506 bodů

Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Mathematics & science Mathematics Applied mathematics

• Plný název: Principal Component Analysis Networks and Algorithms
• Autor: Xiangyu Kong, Changhua Hu, Zhansheng Duan
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 323
• EAN: 9789811029134
• ISBN: 981102913X
• ID: 14279543
• Nakladatelství: Springer Verlag, Singapore
• Hmotnost: 6447 g
• Rozměry: 235 × 155 × 25 mm
• Datum vydání: 13. January 2017

---

---

---