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Stochastic Approximation and Recursive Algorithms and Applications
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Introduction: Applications and Issues
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Chapter 2
Applications to Learning, Repeated Games, State Dependent Noise, and Queue Optimization
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Chapter 3
Applications in Signal Processing, Communications, and Adaptive Control
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Chapter 4
Mathematical Background
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Chapter 5
Convergence with Probability One: Martingale Difference Noise
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Chapter 6
Convergence with Probability One: Correlated Noise
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Chapter 7
Weak Convergence: Introduction
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Chapter 8
Weak Convergence Methods for General Algorithms
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Chapter 9
Applications: Proofs of Convergence
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Chapter 10
Rate of Convergence
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Chapter 11
Averaging of the Iterates
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Chapter 12
Distributed/Decentralized and Asynchronous Algorithms
Overall attention for this book and its chapters
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Mentioned by
syllabi
1
institution with syllabi
wikipedia
6
Wikipedia pages
q&a
1
Q&A thread
Citations
dimensions_citation
392
Dimensions
Readers on
mendeley
94
Mendeley
Book overview
1. Introduction: Applications and Issues
2. Applications to Learning, Repeated Games, State Dependent Noise, and Queue Optimization
3. Applications in Signal Processing, Communications, and Adaptive Control
4. Mathematical Background
5. Convergence with Probability One: Martingale Difference Noise
6. Convergence with Probability One: Correlated Noise
7. Weak Convergence: Introduction
8. Weak Convergence Methods for General Algorithms
9. Applications: Proofs of Convergence
10. Rate of Convergence
11. Averaging of the Iterates
12. Distributed/Decentralized and Asynchronous Algorithms
Summary
Syllabi
Wikipedia
Q&A
Dimensions citations
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
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syllabus from an institution on Open Syllabus Project.
Institution
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Course subject areas covered
Unknown
1
Economics, Business, Engineering, Area and Ethnic Studies