Quantum Inspired Computational Intelligence PDF Download

Author: Siddhartha Bhattacharyya
Publisher: Morgan Kaufmann
ISBN: 9780128044094
Category : Computers
Languages : en
Pages : 0

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Book Description
Quantum Inspired Computational Intelligence: Research and Applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and robust intelligent systems. Conventional computational intelligence-or soft computing-is conjoined with quantum computing to achieve this objective. The models covered can be applied to any endeavor which handles complex and meaningful information.

Author: Leandro dos Santos Coelho
Publisher: Springer Science & Business Media
ISBN: 3540785310
Category : Mathematics
Languages : en
Pages : 168

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Book Description
Research on applying principles of quantum computing to improve the engineering of intelligent systems has been launched since late 1990s. This emergent research field concentrates on studying on quantum computing that is characterized by certain principles of quantum mechanics such as standing waves, interference, quantum bits, coherence, superposition of states, and concept of interference, combined with computational intelligence or soft computing approaches, such as artificial neural networks, fuzzy systems, evolutionary computing, swarm intelligence and hybrid soft computing methods. This volume offers a wide spectrum of research work developed using soft computing combined with quantum computing systems.

Author: Siddhartha Bhattacharyya
Publisher: Morgan Kaufmann
ISBN: 0128044373
Category : Computers
Languages : en
Pages : 506

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Book Description
Quantum Inspired Computational Intelligence: Research and Applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and robust intelligent systems. Conventional computational intelligence—or soft computing—is conjoined with quantum computing to achieve this objective. The models covered can be applied to any endeavor which handles complex and meaningful information. Brings together quantum computing with computational intelligence to achieve enhanced performance and robust solutions Includes numerous case studies, tools, and technologies to apply the concepts to real world practice Provides the missing link between the research and practice

Author: Bhattacharyya, Siddhartha
Publisher: IGI Global
ISBN: 1522552200
Category : Computers
Languages : en
Pages : 329

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Book Description
As multimedia data advances in technology and becomes more complex, the hybridization of soft computing tools allows for more robust and safe solutions in data processing and analysis. Quantum-Inspired Intelligent Systems for Multimedia Data Analysis provides emerging research on techniques used in multimedia information processing using intelligent paradigms including swarm intelligence, neural networks, and deep learning. While highlighting topics such as clustering techniques, neural network architecture, and text data processing, this publication explores the methods and applications of computational intelligent tools. This book is an important resource for academics, computer engineers, IT professionals, students, and researchers seeking current research in the field of multimedia data processing and quantum intelligent systems.

Author: Siddhartha Bhattacharyya
Publisher: CRC Press
ISBN: 042984266X
Category : Computers
Languages : en
Pages : 232

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Book Description
Hybrid computational intelligent techniques are efficient in dealing with the real-world problems encountered in engineering fields. The primary objective of this book is to provide an exhaustive introduction as well as review of the hybrid computational intelligent paradigm, with supportive case studies. In addition, it aims to provide a gallery of engineering applications where this computing paradigm can be effectively use. Finally, it focuses on the recent quantum inspired hybrid intelligence to develop intelligent solutions for the future. The book also incorporates video demonstrations of each application for better understanding of the subject matter.

Author: Shandilya, Shishir K.
Publisher: IGI Global
ISBN: 1522521291
Category : Computers
Languages : en
Pages : 627

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Book Description
Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.

Author: Minrui Fei
Publisher: Springer
ISBN: 3540747699
Category : Computers
Languages : en
Pages : 808

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Book Description
This book is part of a two-volume work that constitutes the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2007, held in Shanghai, China, September 2007. Coverage includes advanced neural network theory, advanced evolutionary computing theory, ant colonies and particle swarm optimization, intelligent modeling, monitoring, and control of complex nonlinear systems, as well as biomedical signal processing, imaging and visualization.

Author: Ashish Khanna
Publisher: Springer Nature
ISBN: 9811584699
Category : Technology & Engineering
Languages : en
Pages : 122

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Book Description
This book gathers the latest quality research work of Ph.D. students working on the current areas presented in the Doctoral Symposium on Computational Intelligence (DoSCI 2020). The book includes works in the areas of artificial intelligence, deep learning, evolutionary algorithms, swarm intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum-inspired computational intelligence, hybrid computational intelligence, machine learning, computer vision, soft computing, distributed computing, parallel and grid computing, cloud computing, high-performance computing, biomedical computing, decision support and decision making. The book is useful for researchers, students, engineers, practitioners and academicians in their advance studies.

Author: Nikola K. Kasabov
Publisher: Springer
ISBN: 3662577151
Category : Technology & Engineering
Languages : en
Pages : 738

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Book Description
Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.

Author: Xin-She Yang
Publisher: Academic Press
ISBN: 0128197145
Category : Computers
Languages : en
Pages : 442

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Book Description
Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others