Cognitive Computing Theory and Applications 1st Edition by Venkat Gudivada, Vijay Raghavan, Venu Govindaraju, Rao ISBN 978-0444637444 0444637443

Cognitive Computing Theory and Applications 1st Edition by Venkat N. Gudivada, Vijay V. Raghavan, Venu Govindaraju, C.R. Rao  – Ebook PDF Instant Download/Delivery: 978-0444637444, 0444637443
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Product details: 

ISBN 10: 0444637443

ISBN 13: 978-0444637444

Author:  Venkat N. Gudivada, Vijay V. Raghavan, Venu Govindaraju, C.R. Rao

Cognitive Computing: Theory and Applications, written by internationally renowned experts, focuses on cognitive computing and its theory and applications, including the use of cognitive computing to manage renewable energy, the environment, and other scarce resources, machine learning models and algorithms, biometrics, Kernel Based Models for transductive learning, neural networks, graph analytics in cyber security, neural networks, data driven speech recognition, and analytical platforms to study the brain-computer interface.

• Comprehensively presents the various aspects of statistical methodology
• Discusses a wide variety of diverse applications and recent developments
• Contributors are internationally renowned experts in their respective areas

Table of contents: 

Section A: Fundamentals and Principles

Chapter 1: Cognitive Computing: Concepts, Architectures, Systems, and Applications

Abstract
1 Introduction
2 Interdisciplinary Nature of Cognitive Science
3 Cognitive Computing Systems
4 Representations for Information and Knowledge
5 Principal Technology Enablers of Cognitive Computing
6 Cognitive Computing Architectures and Approaches
7 Cognitive Computing Systems and Applications
8 Trends and Future Research Directions
9 Cognitive Computing Resources
Chapter 2: Cognitive Computing and Neural Networks: Reverse Engineering the Brain

Abstract
1 Introduction
2 Brain Scalability
3 Neocortical Brain Organization
4 The Concept of a Basic Circuit
5 Abstractions of Cortical Basic Circuits
6 Large-Scale Cortical Simulations
7 Hardware Support for Brain Simulation
8 Deep Learning Networks
9 Summary and Conclusion
Section B: Complex Analytics and Machine Learning

Chapter 3: Visual Analytic Decision-Making Environments for Large-Scale Time-Evolving Graphs

Abstract
1 Introduction
2 Visual Analytics as an Approach to Cognitive Computing
3 Time-Evolving Graphs
4 Visual Analytics as a Framework for Time-Evolving Graphs
5 Visual Analytics Sandbox: An Implementation Architecture
6 Conclusion and Future Research
Acknowledgments
Chapter 4: CyGraph: Graph-Based Analytics and Visualization for Cybersecurity

Abstract
1 Introduction
2 Related Work
3 Description of CyGraph
4 Example Applications
5 Summary
Acknowledgments
Chapter 5: Cognitive Analytics: Going Beyond Big Data Analytics and Machine Learning

Abstract
1 Introduction
2 Evolution of Analytics and Core Themes
3 Types of Learning
4 Machine Learning Algorithms
5 Cognitive Analytics: A Coveted Goal
6 Cognitive Analytics Applications
7 Current Trends and Research Issues
8 Conclusions
Chapter 6: A Cognitive Random Forest: An Intra- and Intercognitive Computing for Big Data Classification Under Cune Condition

Abstract
1 Introduction
2 Terminologies
3 Random Forest Classifiers
4 The STE-M Model
5 Cognitive Random Forest
6 Cognitive Computing System
7 Experimental Validation
8 Conclusions
Chapter 7: Bayesian Additive Regression Tree for Seemingly Unrelated Regression with Automatic Tree Selection

Abstract
1 Introduction
2 BART for SUR with Automatic Tree Selection
3 Fitting BART-SUR Model Through MCMC
4 Simulation Studies
5 Data Analysis
6 Conclusion
Appendices
Section C: Applications

Chapter 8: Cognitive Systems for the Food–Water–Energy Nexus

Abstract
1 Introduction
2 Invariance, Correlation, and Data
3 Time-Series Data
4 Images, Video, and Spatio-Temporal Data
5 Autonomous Systems to Manage Complexity
6 Conclusion
Chapter 9: Cognitive Computing Applications in Education and Learning

Abstract
1 Introduction
2 EDM and LA
3 Recent Research
4 Conclusion
Chapter 10: Large Scale Data Enabled Evolution of Spoken Language Research and Applications

Abstract
1 Introduction
2 Speech Signals
3 Signal Preprocessing
4 Segmental Feature Extraction
5 Prosodic Feature Extraction
6 Mathematical Models
7 Speech Processing Core Tasks and Applications
8 Resources for Speech Research
9 Trends and Research Directions
10 Conclusions
Chapter 11: The Internet of Things and Cognitive Computing

Abstract
1 Introduction
2 The IoT—Definition and History
3 The Role of Big Data
4 Big Data Challenges and Opportunities for IoT and Cognitive Computing
5 IoT Use Cases and Opportunity to Leverage Cognitive Computing
6 Future Opportunities for IoT and Cognitive Computing

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Tags: Venkat Gudivada, Vijay Raghavan, Venu Govindaraju, Rao, Cognitive Computing, Theory and Applications