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<title>Complex Networks: A Networking and Signal Processing Perspective - Contents</title>
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<font size="10" style="color:#527bbd"><b>Complex Networks</b></font></br>
<h1 style="margin-top: -10px">A Networking and Signal Processing Perspective</h1>
<h1><a href="images/Contents_ComplexNetworks_PHPTR_2018_Manoj_Chakraborty_Singh.pdf" target="_blank">Contents</a></h1>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Preamble</u></b></font></br></summary>
<p> </p>
<ul><li><p> Preface </p></li></ul>
<ul><li><p> Acknowledgments </p></li></ul>
<ul><li><p> About the Authors </p></li></ul>
<ul><li><p> About the Cover </ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 1: Introduction</u></b></font></br></summary>
<p> </p>
<ul><li><p> Complex Networks </p></li></ul>
<ul><li><p> Types of Complex Networks </p></li></ul>
<ul><li><p> Benefits of Studying Complex Networks </p></li></ul>
<ul><li><p> Challenges in Studying Complex Networks </p></li></ul>
<ul><li><p> What This Book Offers </p></li></ul>
<ul><li><p> Organization of the Book </p></li></ul>
<ul><li><p> Support Materials Available for Instructors </p></li></ul>
<ul><li><p> Summary </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 2: Graph Theory Preliminaries</u></b></font></br></summary>
<p> </p>
<ul><li><p> Introduction </p></li></ul>
<ul><li><p> Graphs </p></li></ul>
<ul><li><p> Matrices Related to a Graph </p></li></ul>
<ul><li><p> Basic Graph Metrics </p></li></ul>
<ul><li><p> Basic Graph Definitions and Properties </p></li></ul>
<ul><li><p> Types of Graphs </p></li></ul>
<ul><li><p> Other Important Measures for Graphs </p></li></ul>
<ul><li><p> Graph Pathfinding Algorithms </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 3: Introduction to Complex Networks</u></b></font></br></summary>
<p> </p>
<ul><li><p> Major Types of Complex Networks </p></li></ul>
<ul><li><p> Complex Network Metrics </p></li></ul>
<ul><li><p> Community Detection in Complex Networks</p></li></ul>
<ul><li><p> Entropy in Complex Network </p></li></ul>
<ul><li><p> Random Networks </p></li></ul>
<ul><li><p> Open Research Issues </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 4: Small-World Networks</u></b></font></br></summary>
<p> </p>
<ul><li><p> Introduction </p></li></ul>
<ul><li><p> Milgram’s Small-World Experiment </p></li></ul>
<ul><li><p> Characteristics of Small-World Networks</p></li></ul>
<ul><li><p> Real-World Small-World Networks </p></li></ul>
<ul><li><p> Creation and Evolution of Small-World Networks </p></li></ul>
<ul><li><p> Capacity-Based Deterministic Addition of New Links </p></li></ul>
<ul><li><p> Creation of Deterministic Small-World Networks </p></li></ul>
<ul><li><p> Anchor Points in a String Topology Small-World Network </p></li></ul>
<ul><li><p> Heuristic Approach-Based Deterministic Link Addition </p></li></ul>
<ul><li><p> Routing in Small-World Networks </p></li></ul>
<ul><li><p> Capacity of Small-World Networks </p></li></ul>
<ul><li><p> Open Research Issues </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 5: Scale-Free Networks</u></b></font></br></summary>
<p> </p>
<ul><li><p> Introduction </p></li></ul>
<ul><li><p> Characteristics of Scale-Free Networks</p></li></ul>
<ul><li><p> Real-World Scale-Free Networks</p></li></ul>
<ul><li><p> Scale-Free Network Formation </p></li></ul>
<ul><li><p> Preferential Attachment–Based Scale-Free Network Creation </p></li></ul>
<ul><li><p> Fitness-Based Scale-Free Network Creation </p></li></ul>
<ul><li><p> Varying Intrinsic Fitness-Based Scale-Free Network Creation </p></li></ul>
<ul><li><p> Optimization-Based Scale-Free Network Creation </p></li></ul>
<ul><li><p> Scale-Free Network Creation with Exponent 1</p></li></ul>
<ul><li><p> Greedy Global Decision–Based Scale-Free Network Creation </p></li></ul>
<ul><li><p> Deterministic Scale-Free Network Creation</p></li></ul>
<ul><li><p> Open Research Issues </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 6: Small-World Wireless Mesh Networks</u></b></font></br></summary>
<p> </p>
<ul><li><p> Introduction </p></li></ul>
<ul><li><p> Classification of Small-World Wireless Mesh Networks </p></li></ul>
<ul><li><p> Creation of Random Long-Ranged Links </p></li></ul>
<ul><li><p> Small-World Based on Pure Random Link Addition </p></li></ul>
<ul><li><p> Small-World Based on Euclidean Distance </p></li></ul>
<ul><li><p> Realization of Small-World Networks Based on Antenna Metrics </p></li></ul>
<ul><li><p> Algorithmic Approaches to Create Small-World Wireless Mesh Networks </p></li></ul>
<ul><li><p> Gateway-Router-Centric Small-World Network Formation </p></li></ul>
<ul><li><p> Creation of Deterministic Small-World Wireless Mesh Networks </p></li></ul>
<ul><li><p> Creation of Non-Persistent Small-World Wireless Mesh Networks </p></li></ul>
<ul><li><p> Non-Persistent Routing in Small-World Wireless Mesh Networks </p></li></ul>
<ul><li><p> Qualitative Comparison of Existing Solutions </p></li></ul>
<ul><li><p> Open Research Issues </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 7: Small-World Wireless Sensor Networks</u></b></font></br></summary>
<p> </p>
<ul><li><p> Introduction </p></li></ul>
<ul><li><p> Small-World Wireless Mesh Networks vs. Small-World Wireless Sensor Networks </p></li></ul>
<ul><li><p> Why Small-World Wireless Sensor Networks? </p></li></ul>
<ul><li><p> Challenges in Transforming WSNs to SWWSNs </p></li></ul>
<ul><li><p> Types of Long-Ranged Links for SWWSNs </p></li></ul>
<ul><li><p> Approaches for Transforming WSNs to SWWSNs </p></li></ul>
<ul><li><p> SWWSNs with Wired LLs </p></li></ul>
<ul><li><p> Open Research Issues </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 8: Spectra of Complex Networks</u></b></font></br></summary>
<p> </p>
<ul><li><p> Introduction </p></li></ul>
<ul><li><p> Spectrum of a Graph </p></li></ul>
<ul><li><p> Adjacency Matrix Spectrum of a Graph</p></li></ul>
<ul><li><p> Adjacency Matrix Spectra of Complex Networks </p></li></ul>
<ul><li><p> Laplacian Spectrum of a Graph </p></li></ul>
<ul><li><p> Laplacian Spectra of Complex Networks </p></li></ul>
<ul><li><p> Network Classification Using Spectral Densities </p></li></ul>
<ul><li><p> Open Research Issues </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 9: Signal Processing on Complex Networks</u></b></font></br></summary>
<p> </p>
<ul><li><p> Introduction to Graph Signal Processing </p></li></ul>
<ul><li><p> Comparison between Classical and Graph Signal Processing </p></li></ul>
<ul><li><p> The Graph Laplacian as an Operator </p></li></ul>
<ul><li><p> Quantifying Variations in Graph Signals </p></li></ul>
<ul><li><p> Graph Fourier Transform </p></li></ul>
<ul><li><p> Generalized Operators for Graph Signals</p></li></ul>
<ul><li><p> Applications </p></li></ul>
<ul><li><p> Windowed Graph Fourier Transform </p></li></ul>
<ul><li><p> Open Research Issues </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 10: Graph Signal Processing Approaches</u></b></font></br></summary>
<p> </p>
<ul><li><p> Introduction </p></li></ul>
<ul><li><p> Graph Signal Processing Based on Laplacian Matrix</p></li></ul>
<ul><li><p> DSPG Framework </p></li></ul>
<ul><li><p> DSPG Framework Based on Weight Matrix </p></li></ul>
<ul><li><p> DSPG Framework Based on Directed Laplacian </p></li></ul>
<ul><li><p> Comparison of Graph Signal Processing Approaches </p></li></ul>
<ul><li><p> Open Research Issues </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Chapter 11: Multiscale Analysis of Complex Networks</u></b></font></br></summary>
<p> </p>
<ul><li><p> Introduction </p></li></ul>
<ul><li><p> Multiscale Transforms for Complex Network Data </p></li></ul>
<ul><li><p> Crovella and Kolaczyk Wavelet Transform </p></li></ul>
<ul><li><p> Random Transform </p></li></ul>
<ul><li><p> Lifting-Based Wavelets</p></li></ul>
<ul><li><p> Two-Channel Graph Wavelet Filter Banks </p></li></ul>
<ul><li><p> Spectral Graph Wavelet Transform </p></li></ul>
<ul><li><p> Spectral Graph Wavelet Transform Based on Directed Laplacian </p></li></ul>
<ul><li><p> Diffusion Wavelets </p></li></ul>
<ul><li><p> Open Research Issues </p></li></ul>
<ul><li><p> Summary </p></li></ul>
<ul><li><p> Exercises </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Appendices</u></b></font></br></summary>
<p> </p>
<ul><li><p> Vectors and Matrices </p></li></ul>
<ul><li><p> Classical Signal Processing </p></li></ul>
<ul><li><p> Analysis of Locations of Anchor Points </p></li></ul>
<ul><li><p> Asymptotic Behavior of Functions </p></li></ul>
<ul><li><p> Relevant Academic Courses and Programs</p></li></ul>
<ul><li><p> Relevant Journals and Conferences </p></li></ul>
<ul><li><p> Relevant Datasets and Visualization Tools </p></li></ul>
<ul><li><p> Relevant Research Groups </p></li></ul>
</details>
<p> </p>
<details>
<summary><font size="4" style="color:#527bbd"><b><u>Epilogue</u></b></font></br></summary>
<p> </p>
<ul><li><p>Notation</p></li></ul>
<ul><li><p>Acronyms</p></li></ul>
<ul><li><p>Bibliography</p></li></ul>
<ul><li><p>Index</ul>
</details>
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<p>Copyright © by B. S. Manoj, Abhishek Chakraborty, and Rahul singh - All rights reserved. </a></span></p>
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