Cognitive Computing Models in Communication Systems

✍ Scribed by Budati Anil Kumar, S. B. Goyal, Sardar M. N. Islam

• Publisher: Wiley-Scrivener
• Year: 2022
• Tongue: English
• Leaves: 231
• Series: Smart and Sustainable Intelligent Systems
• Category: Library

✦ Synopsis

COGNITIVE COMPUTING MODELS IN COMMUNICATION SYSTEMS

A concise book on the latest research focusing on problems and challenges in the areas of data transmission technology, computer algorithms, AI-based devices, computer technology, and their solutions.

The book provides a comprehensive overview of state-of-the-art research work on cognitive models in communication systems and computing techniques. It also bridges the gap between various communication systems and solutions by providing the current models and computing techniques, their applications, the strengths and limitations of the existing methods, and the future directions in this area.

The contributors showcase their latest research work focusing on the issues, challenges, and solutions in the field of data transmission techniques, computational algorithms, artificial intelligence (AI)-based devices, and computing techniques.

Readers will find in this succinctly written and unique book:

• Topics covering the applications of advanced cognitive devices, models, architecture, and techniques.
• A range of case studies and applications that will provide readers with the tools to apply cutting-edge models and algorithms.
• In-depth information about new cognitive computing models and conceptual frameworks and their implementation.

Audience

The book is designed for researchers and electronics engineers, computer science engineers, industrial engineers, and mechanical engineers (both in academia and industry) working in the fields of machine learning, cognitive computing, mobile communication, and wireless network system.

✦ Table of Contents

Cover
Half-Title Page
Series Page
Title Page
Copyright Page
Contents
Preface
Acknowledgement
1 Design of a Low-Voltage LDO of CMOS Voltage Regulator for Wireless Communications
1.1 Introduction
1.2 LDO Controller Arrangement and Diagram Drawing
1.2.1 Design of the LDO Regulator
1.2.1.1 Design of the Fault Amplifier
1.2.1.2 Design of the MPT Phase
1.3 Conclusion
References
2 Performance Analysis of Machine Learning and Deep Learning Algorithms for Smart Cities: The Present State and Future Directions
2.1 Introduction
2.2 Smart City: The Concept
2.3 Application Layer
2.3.1 Smart Homes and Buildings
2.3.1.1 Smart Surveillance
2.3.2 Smart Transportation and Driving
2.3.3 Smart Healthcare
2.3.4 Smart Parking
2.3.5 Smart Grid
2.3.6 Smart Farming
2.3.7 Sensing Layer
2.3.8 Communication Layer
2.3.9 Data Layer
2.3.10 Security Layer
2.4 Issues and Challenges in Smart Cities: An Overview
2.5 Machine Learning: An Overview
2.5.1 Supervised Learning
2.5.2 Support Vector Machines (SVMs)
2.5.3 Artificial Neural Networks
2.5.4 Random Forest
2.5.5 Naïve Bayes
2.6 Unsupervised Learning
2.7 Deep Learning: An Overview
2.7.1 Autoencoder
2.7.2 Convolution Neural Networks (CNNs)
2.7.3 Recurrent Neural Networks (RNNs)
2.8 Deep Learning vs Machine Learning
2.9 Smart Healthcare
2.9.1 Evolution Toward a Smart Healthcare Framework
2.9.2 Application of ML/DL in Smart Healthcare
2.10 Smart Transport System
2.10.1 Evolution Toward a Smart Transport System
2.10.2 Application of ML/DL in a Smart Transportation System
2.11 Smart Grids
2.11.1 Evolution Toward Smart Grids
2.11.2 Application of ML/DL in Smart Grids
2.12 Challenges and Future Directions
2.13 Conclusion
References
3 Application of Machine Learning Algorithms and Models in 3D Printing
3.1 Introduction
3.2 Literature Review
3.3 Methods and Materials
3.4 Results and Discussion
3.5 Conclusion
References
4 A Novel Model for Optimal Reliable Routing Path Prediction in MANET
4.1 Introduction
4.2 Analytical Hierarchical Process Technique
4.3 Mathematical Models and Protocols
4.3.1 Rough Sets
4.3.1.1 Pawlak Rough Set Theory Definitions
4.3.2 Fuzzy TOPSIS
4.4 Routing Protocols
4.4.1 Classification of Routing Paths
4.5 RTF-AHP Model
4.5.1 Rough TOPSIS Fuzzy Set Analytical Hierarchical Process Algorithm
4.6 Models for Optimal Routing Performance
4.6.1 Genetic Algorithm Technique
4.6.2 Ant Colony Optimization Technique
4.6.3 RTF-AHP Model Architecture Flow
4.7 Results and Discussion
4.8 Conclusion
References
5 IoT-Based Smart Traffic Light Control
5.1 Introduction
5.2 Scope of the Proposed Work
5.3 Proposed System Implementation
5.4 Testing and Results
5.5 Test Results
5.6 Conclusions
References
6 Differential Query Execution on Privacy Preserving Data Distributed Over Hybrid Cloud
6.1 Introduction
6.2 Related Work
6.3 Proposed Solution
6.3.1 Data Transformation
6.3.2 Data Distribution
6.3.3 Query Execution
6.4 Novelty in the Proposed Solution
6.5 Results
6.6 Conclusion
References
7 Design of CMOS Base Band Analog
7.1 Introduction
7.2 Proposed Technique of the BBA Chain for Reducing Energy Consumption
7.3 Channel Preference Filter
7.4 Programmable Amplifier Gain
7.5 Executed Outcomes
7.6 Conclusion
References
8 Review on Detection of Neuromuscular Disorders Using Electromyography
8.1 Introduction
8.2 Materials
8.3 Methods
8.4 Conclusion
References
9 Design of Complementary Metal– Oxide Semiconductor Ring Modulator by Built-In Thermal Tuning
9.1 Introduction
9.2 Device Structure
9.3 DC Performance
9.4 Small-Signal Radiofrequency Assessments
9.5 Data Modulation Operation (High Speed)
9.6 Conclusions and Acknowledgments
References
10 Low-Power CMOS VCO Used in RF Transmitter
10.1 Introduction
10.2 Transmitter Architecture
10.3 Voltage-Controlled Ring Oscillator Design
10.4 CMOS Combiner
10.5 Conclusion
References
11 A Novel Low-Power FrequencyModulated Continuous Wave Radar Based on Low-Noise Mixer
11.1 Introduction
11.2 FMCW Principle
11.3 Results
11.4 Conclusion
References
12 A Highly Integrated CMOS RF Tx Used for IEEE 802.15.4
12.1 Introduction
12.2 Related Work
12.3 Simulation Results and Discussion
12.4 Conclusion
References
13 A Novel Feedforward Offset Cancellation Limiting Amplifier in Radio Frequencies
13.1 Introduction
13.2 Hardware Design
13.2.1 Limiting Amplifier
13.2.2 Offset Extractor
13.2.3 Architecture and Gain
13.2.4 Quadrature Detector
13.2.5 Sensitivity
13.3 Experimental Results
13.4 Conclusion
References
14 A Secured Node Authentication and Access Control Model for IoT Smart Home Using Double-Hashed Unique Labeled Key-Based Validation
14.1 Introduction
14.2 Challenges in IoT Security and Privacy
14.2.1 Heterogeneous Communication and Devices
14.2.2 Physical Equipment Integration
14.2.3 Resource Handling Limitations
14.2.4 Wide Scale
14.2.5 Database
14.3 Background
14.4 Proposed Model
14.4.1 Communication Flow
14.4.1.1 IoT Node and Registration Authority
14.4.1.2 User and Local Authorization Authority
14.5 Results
14.6 Conclusion
14.7 Claims
References
Index