Brain and Nature Inspired Learning Computation and Recognition

Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature. Sections cover new developments and main applications, algorithms and simulations. Developments in brain and nature-inspired learning have promoted interest in image processing, clustering problems, change detection, control theory and other disciplines. The book discusses the main problems and applications pertaining to bio-inspired computation and recognition, introducing algorithm implementation, model simulation, and practical application of parameter setting. Readers will find solutions to problems in computation and recognition, particularly neural networks, natural computing, machine learning and compressed sensing. This volume offers a comprehensive and well-structured introduction to brain and nature-inspired learning, computation, and recognition. Presents an invaluable systematic introduction to brain and nature-inspired learning, computation and recognition Describes the biological mechanisms, mathematical analyses and scientific principles behind brain and nature-inspired learning, calculation and recognition Systematically analyzes neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature Discusses the theory and application of algorithms and neural networks, natural computing, machine learning and compression perception

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  • Author : Licheng Jiao
  • Publisher : Elsevier
  • Pages : 788 pages
  • ISBN : 0128204044
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKBrain and Nature Inspired Learning Computation and Recognition

Brain and Nature-Inspired Learning, Computation and Recognition

Brain and Nature-Inspired Learning, Computation and Recognition
  • Author : Licheng Jiao,Ronghua Shang,Fang Liu,Weitong Zhang
  • Publisher : Elsevier
  • Release : 18 January 2020
GET THIS BOOKBrain and Nature-Inspired Learning, Computation and Recognition

Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature. Sections cover new developments and main applications, algorithms and simulations. Developments in brain and nature-inspired learning have promoted interest in image processing, clustering problems, change detection, control theory and other disciplines. The book discusses the main problems and applications pertaining to bio-inspired computation and recognition, introducing algorithm

Artificial Intelligence in the Age of Neural Networks and Brain Computing

Artificial Intelligence in the Age of Neural Networks and Brain Computing
  • Author : Robert Kozma,Cesare Alippi,Yoonsuck Choe,Francesco Carlo Morabito
  • Publisher : Academic Press
  • Release : 30 October 2018
GET THIS BOOKArtificial Intelligence in the Age of Neural Networks and Brain Computing

Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity and smart autonomous search engines. The book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. The success of AI-based commercial products

Nature-Inspired Computing Design, Development, and Applications

Nature-Inspired Computing Design, Development, and Applications
  • Author : Nunes de Castro, Leandro
  • Publisher : IGI Global
  • Release : 31 May 2012
GET THIS BOOKNature-Inspired Computing Design, Development, and Applications

The observation of nature has been the inspiration for many materials, laws, and theories, as well as computational methods. Nature-Inspired computing Design, Development, and Applications covers all the main areas of natural computing, from methods to computationally synthesized natural phenomena, to computing paradigms based on natural materials. This volume is comprised of ideas and research from nature to develop computational systems or materials to perform computation. Researchers, academic educators, and professionals will find a comprehensive view of all aspects of

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications
  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release : 26 July 2016
GET THIS BOOKNature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating

Nature-Inspired Computation and Machine Learning

Nature-Inspired Computation and Machine Learning
  • Author : Alexander Gelbukh,Félix Castro Espinoza,Sofía N. Galicia-Haro
  • Publisher : Springer
  • Release : 05 November 2014
GET THIS BOOKNature-Inspired Computation and Machine Learning

The two-volume set LNAI 8856 and LNAI 8857 constitutes the proceedings of the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. The total of 87 papers plus 1 invited talk presented in these proceedings were carefully reviewed and selected from 348 submissions. The first volume deals with advances in human-inspired computing and its applications. It contains 44 papers structured into seven sections: natural language processing, natural language processing applications, opinion mining, sentiment analysis, and social network applications, computer vision, image

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications
  • Author : Modestus O. Okwu,Lagouge K. Tartibu
  • Publisher : Springer Nature
  • Release : 13 November 2020
GET THIS BOOKMetaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm,

Computational Vision and Bio-Inspired Computing

Computational Vision and Bio-Inspired Computing
  • Author : S. Smys,João Manuel R. S. Tavares,Valentina Emilia Balas,Abdullah M. Iliyasu
  • Publisher : Springer Nature
  • Release : 06 January 2020
GET THIS BOOKComputational Vision and Bio-Inspired Computing

This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. Due to the rapid advances in the emerging information, communication and computing technologies, the Internet of Things, cloud and edge computing, and artificial intelligence play a significant role in the computational vision context. In recent years, computational vision has contributed to enhancing the methods of controlling the operations in biological systems, like ant colony optimization, neural networks, and immune systems. Moreover, the ability of computational vision to

Bio-inspired Neurocomputing

Bio-inspired Neurocomputing
  • Author : Akash Kumar Bhoi,Pradeep Kumar Mallick,Chuan-Ming Liu,Valentina E. Balas
  • Publisher : Springer Nature
  • Release : 21 July 2020
GET THIS BOOKBio-inspired Neurocomputing

This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken

Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence
  • Author : Nikola K. Kasabov
  • Publisher : Springer
  • Release : 29 August 2018
GET THIS BOOKTime-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

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

Intelligent Computing Theories and Methodologies

Intelligent Computing Theories and Methodologies
  • Author : De-Shuang Huang,Vitoantonio Bevilacqua,Prashan Premaratne
  • Publisher : Springer
  • Release : 10 August 2015
GET THIS BOOKIntelligent Computing Theories and Methodologies

This two-volume set LNCS 9225 and LNCS 9226 constitutes - in conjunction with the volume LNAI 9227 - the refereed proceedings of the 11th International Conference on Intelligent Computing, ICIC 2015, held in Fuzhou, China, in August 2015. The total of 191 full and 42 short papers presented in the three ICIC 2015 volumes was carefully reviewed and selected from 671 submissions. The papers are organized in topical sections such as evolutionary computation and learning; compressed sensing, sparse coding and social computing; neural networks, nature inspired computing and optimization;

Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms

Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms
  • Author : Dash, Sujata,Tripathy, B.K.,Rahman, Atta ur
  • Publisher : IGI Global
  • Release : 10 August 2017
GET THIS BOOKHandbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms

The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference

Brain-Inspired Information Technology

Brain-Inspired Information Technology
  • Author : Akitoshi Hanazawa,Tsutom Miki,Keiichi Horio
  • Publisher : Springer Science & Business Media
  • Release : 22 September 2010
GET THIS BOOKBrain-Inspired Information Technology

"Brain-inspired information technology" is one of key concepts for the development of information technology in the next generation. Explosive progress of computer technology has been continuing based on a simple principle called "if-then rule". This means that the programmer of software have to direct every action of the computer programs in response to various inputs. There inherently is a limitation of complexity because we human have a limited capacity for managing complex systems. Actually, many bugs, mistakes of programming, exist

The Deep Learning Revolution

The Deep Learning Revolution
  • Author : Terrence J. Sejnowski
  • Publisher : MIT Press
  • Release : 23 October 2018
GET THIS BOOKThe Deep Learning Revolution

How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains

Nature Inspired Problem-Solving Methods in Knowledge Engineering

Nature Inspired Problem-Solving Methods in Knowledge Engineering
  • Author : José Mira,José R. Álvarez
  • Publisher : Springer
  • Release : 23 June 2007
GET THIS BOOKNature Inspired Problem-Solving Methods in Knowledge Engineering

The second of a two-volume set, this book constitutes the refereed proceedings of the Second International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2007, held in La Manga del Mar Menor, Spain in June 2007. It contains all the contributions connected with biologically inspired methods and techniques for solving AI and knowledge engineering problems in different application domains.