Nature-Inspired Computation

Mario D’Acunto, PhD
Consiglio Nazionale delle Ricerche, Istituto di Scienze e Tecnologie dell’Informazione, Pisa, Italy

Series: Computer Science, Technology and Applications
BISAC: COM014000

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$192.00

Volume 10

Issue 1

Volume 2

Volume 3

Special issue: Resilience in breaking the cycle of children’s environmental health disparities
Edited by I Leslie Rubin, Robert J Geller, Abby Mutic, Benjamin A Gitterman, Nathan Mutic, Wayne Garfinkel, Claire D Coles, Kurt Martinuzzi, and Joav Merrick

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Nature inspired computation is an old idea, first proposed in the early fifties by Alan Turing, one of the founders of computer science. Turing suggested computational models of pattern formation in living systems based on systems of coupled reaction-diffusion equations giving rise to spatial patterns due to self-organization of substances in chemical concentrations. Since the pioneering work by Turing, many optimization algorithms stimulated by real-world features have gained great popularity and impact, thanks to their efficiency in solving nonlinear design problems.

Nature-inspired computation has permeated into almost all areas of sciences, engineering and industries, from data mining to optimization, from computational intelligence to signal processing, from image analysis and vision systems to industrial applications. This book provides an introductory tour of computational strategies. The book is subdivided in two parts, briefly describing the inspiration and motivation of natural processes and phenomena, main players, design principles, the scope of each branch, current trends and open problems.

In the first section, attention is focused on Artificial and Spiking Neural Networks (Chapter 2), Evolutionary and Genetic Algorithms (Chapter 3), and Swarm Intelligence algorithms (Chapter 4). In the second section, we present the emergent knowledge and technologies in Multiscale Nature processes (Chapter 5), Quantum Computing and Quantum Cryptography (Chapter 6), Encryption and Secure Communication system (Chapter 7), Image processing and Vision systems (Chapter 8), and finally on Nanophotonics Information (Chapter 9). (Imprint: Nova)

Preface

Chapter 1. Introduction: Taking Inspiration from Nature to Solve Computation Problems

Chapter 2. Artificial and Spiking Neural Networks

Chapter 3. Genetic and Evolutionary Computation

Chapter 4. Machine Learning and Swarm Intelligence

Chapter 5. Nanostructures Inspiring Computation

Chapter 6. Quantum Computing

Chapter 7. Encryption Using Chaos, Noise and Oscillator Synchronization

Chapter 8. Nature-Inspired Computation from Image Analysis and Vision Systems

Chapter 9. Nano-Optics and Nano-Photonics Information: Computation Inspired by Light-Matter Interaction at Nanoscale

Index

The book has been written by a scientist working at the edge between nanophysics and computer science; professional people or groups that can benefit from the book are scientist and university or college students involved in the fields of mathematics, communication engineering, physics, biologists, computer scientists. The book is rather popular as impact, so any curious reader can be considered a potential end user.

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