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This book provides a broad yet detailed introduction to neural
networks and machine learning in a statistical framework. A single,
comprehensive resource for study and further research, it explores
the major popular neural network models and statistical learning
approaches with examples and exercises and allows readers to gain a
practical working understanding of the content. This updated new
edition presents recently published results and includes six new
chapters that correspond to the recent advances in computational
learning theory, sparse coding, deep learning, big data and cloud
computing. Each chapter features state-of-the-art descriptions and
significant research findings. The topics covered include: *
multilayer perceptron; * the Hopfield network; * associative memory
models;* clustering models and algorithms; * t he radial basis
function network; * recurrent neural networks; * nonnegative matrix
factorization; * independent component analysis; *probabilistic and
Bayesian networks; and * fuzzy sets and logic. Focusing on the
prominent accomplishments and their practical aspects, this book
provides academic and technical staff, as well as graduate students
and researchers with a solid foundation and comprehensive reference
on the fields of neural networks, pattern recognition, signal
processing, and machine learning.
This textbook provides a comprehensive introduction to
nature-inspired metaheuristic methods for search and optimization,
including the latest trends in evolutionary algorithms and other
forms of natural computing. Over 100 different types of these
methods are discussed in detail. The authors emphasize non-standard
optimization problems and utilize a natural approach to the topic,
moving from basic notions to more complex ones. An introductory
chapter covers the necessary biological and mathematical
backgrounds for understanding the main material. Subsequent
chapters then explore almost all of the major metaheuristics for
search and optimization created based on natural phenomena,
including simulated annealing, recurrent neural networks, genetic
algorithms and genetic programming, differential evolution, memetic
algorithms, particle swarm optimization, artificial immune systems,
ant colony optimization, tabu search and scatter search, bee and
bacteria foraging algorithms, harmony search, biomolecular
computing, quantum computing, and many others. General topics on
dynamic, multimodal, constrained, and multiobjective optimizations
are also described. Each chapter includes detailed flowcharts that
illustrate specific algorithms and exercises that reinforce
important topics. Introduced in the appendix are some benchmarks
for the evaluation of metaheuristics. Search and Optimization by
Metaheuristics is intended primarily as a textbook for graduate and
advanced undergraduate students specializing in engineering and
computer science. It will also serve as a valuable resource for
scientists and researchers working in these areas, as well as those
who are interested in search and optimization methods.
Providing a broad but in-depth introduction to neural network and
machine learning in a statistical framework, this book provides a
single, comprehensive resource for study and further research. All
the major popular neural network models and statistical learning
approaches are covered with examples and exercises in every chapter
to develop a practical working understanding of the content. Each
of the twenty-five chapters includes state-of-the-art descriptions
and important research results on the respective topics. The broad
coverage includes the multilayer perceptron, the Hopfield network,
associative memory models, clustering models and algorithms, the
radial basis function network, recurrent neural networks, principal
component analysis, nonnegative matrix factorization, independent
component analysis, discriminant analysis, support vector machines,
kernel methods, reinforcement learning, probabilistic and Bayesian
networks, data fusion and ensemble learning, fuzzy sets and logic,
neurofuzzy models, hardware implementations, and some machine
learning topics. Applications to biometric/bioinformatics and data
mining are also included. Focusing on the prominent accomplishments
and their practical aspects, academic and technical staff, graduate
students and researchers will find that this provides a solid
foundation and encompassing reference for the fields of neural
networks, pattern recognition, signal processing, machine learning,
computational intelligence, and data mining.
This concise but comprehensive textbook reviews the most popular
neural-network methods and their associated techniques. Each
chapter provides state-of-the-art descriptions of important major
research results of the respective neural-network methods. A range
of relevant computational intelligence topics, such as fuzzy logic
and evolutionary algorithms - powerful tools for neural-network
learning - are introduced. The systematic survey of neural-network
models and exhaustive references list will point readers toward
topics for future research. The algorithms outlined also make this
textbook a valuable reference for scientists and practitioners
working in pattern recognition, signal processing, speech and image
processing, data analysis and artificial intelligence.
This concise but comprehensive textbook reviews the most popular
neural-network methods and their associated techniques. Each
chapter provides state-of-the-art descriptions of important major
research results of the respective neural-network methods. A range
of relevant computational intelligence topics, such as fuzzy logic
and evolutionary algorithms - powerful tools for neural-network
learning - are introduced. The systematic survey of neural-network
models and exhaustive references list will point readers toward
topics for future research. The algorithms outlined also make this
textbook a valuable reference for scientists and practitioners
working in pattern recognition, signal processing, speech and image
processing, data analysis and artificial intelligence.
This book gathers selected papers presented at the International
Conference on Sentimental Analysis and Deep Learning (ICSADL 2021),
jointly organized by Tribhuvan University, Nepal; Prince of Songkla
University, Thailand; and Ejesra during June, 18-19, 2021. The
volume discusses state-of-the-art research works on incorporating
artificial intelligence models like deep learning techniques for
intelligent sentiment analysis applications. Emotions and
sentiments are emerging as the most important human factors to
understand the prominent user-generated semantics and perceptions
from the humongous volume of user-generated data. In this scenario,
sentiment analysis emerges as a significant breakthrough
technology, which can automatically analyze the human emotions in
the data-driven applications. Sentiment analysis gains the ability
to sense the existing voluminous unstructured data and delivers a
real-time analysis to efficiently automate the business processes.
Meanwhile, deep learning emerges as the revolutionary paradigm with
its extensive data-driven representation learning architectures.
This book discusses all theoretical aspects of sentimental
analysis, deep learning and related topics.
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Computer and Communication Engineering - Third International Conference, CCCE 2023, Stockholm, Sweden, March 10–12, 2023, Revised Selected Papers (1st ed. 2023)
Filippo Neri, Ke-Lin Du, Vijayakumar Varadarajan, Angel-Antonio San-Blas, Zhiyu Jiang
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R2,306
Discovery Miles 23 060
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Ships in 10 - 15 working days
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This book constitutes refereed proceedings of the Third
International Conference on Computer and Communication Engineering,
CCCE 2023, held in Stockholm, Sweden, in March 2023. The 18 full
papers presented were carefully reviewed and selected from 36
submissions. The papers are organized in the following topical
sections: image analysis and method; network model and function
analysis of mobile network; system security estimation and analysis
of data network; and AI-based system model and algorithm.
This book mainly reflects the recent research works in evolutionary
computation technologies and mobile sustainable networks with a
specific focus on computational intelligence and communication
technologies that widely ranges from theoretical foundations to
practical applications in enhancing the sustainability of mobile
networks. Today, network sustainability has become a significant
research domain in both academia and industries present across the
globe. Also, the network sustainability paradigm has generated a
solution for existing optimization challenges in mobile
communication networks. Recently, the research advances in
evolutionary computing technologies including swarm intelligence
algorithms and other evolutionary algorithm paradigms are
considered as the widely accepted descriptors for mobile
sustainable networks virtualization, optimization, and automation.
To deal with the emerging impacts on mobile communication networks,
this book discusses about the state-of-the research works on
developing a sustainable design and their implementation in mobile
networks. With the advent of evolutionary computation algorithms,
this book contributes varied research chapters to develop a new
perspective on mobile sustainable networks.
This book includes high quality research papers presented at the
International Conference on Communication, Computing and
Electronics Systems 2021, held at the PPG Institute of Technology,
Coimbatore, India, on 28-29 October 2021. The volume focuses mainly
on the research trends in cloud computing, mobile computing,
artificial intelligence and advanced electronics systems. The
topics covered are automation, VLSI, embedded systems, optical
communication, RF communication, microwave engineering, artificial
intelligence, deep learning, pattern recognition, communication
networks, Internet of Things, cyber-physical systems, and
healthcare informatics.
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Computer and Communication Engineering - 2nd International Conference, CCCE 2022, Rome, Italy, March 11-13, 2022, Revised Selected Papers (Paperback, 1st ed. 2022)
Filippo Neri, Ke-Lin Du, Vijayakumar Varadarajan, San-Blas Angel-Antonio, Zhiyu Jiang
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R1,528
Discovery Miles 15 280
|
Ships in 10 - 15 working days
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This book constitutes refereed proceedings of the 2nd International
Conference on Computer and Communication Engineering, CCCE 2022,
held in Rome, Italy, March 11-13, 2022. The 9 full papers and 8
short papers presented in this volume were carefully reviewed and
selected from a total of 36 submissions. The papers in the volume
are organised according to the following topical headings:
information science and mobile communication; computer and
electronic engineering.
This book mainly reflects the recent research works in evolutionary
computation technologies and mobile sustainable networks with a
specific focus on computational intelligence and communication
technologies that widely ranges from theoretical foundations to
practical applications in enhancing the sustainability of mobile
networks. Today, network sustainability has become a significant
research domain in both academia and industries present across the
globe. Also, the network sustainability paradigm has generated a
solution for existing optimization challenges in mobile
communication networks. Recently, the research advances in
evolutionary computing technologies including swarm intelligence
algorithms and other evolutionary algorithm paradigms are
considered as the widely accepted descriptors for mobile
sustainable networks virtualization, optimization, and automation.
To deal with the emerging impacts on mobile communication networks,
this book discusses about the state-of-the research works on
developing a sustainable design and their implementation in mobile
networks. With the advent of evolutionary computation algorithms,
this book contributes varied research chapters to develop a new
perspective on mobile sustainable networks.
This book includes high quality research papers presented at the
International Conference on Communication, Computing and
Electronics Systems 2021, held at the PPG Institute of Technology,
Coimbatore, India, on 28-29 October 2021. The volume focuses mainly
on the research trends in cloud computing, mobile computing,
artificial intelligence and advanced electronics systems. The
topics covered are automation, VLSI, embedded systems, optical
communication, RF communication, microwave engineering, artificial
intelligence, deep learning, pattern recognition, communication
networks, Internet of Things, cyber-physical systems, and
healthcare informatics.
This book features high-quality research papers presented at the
2nd International Conference on Sustainable Expert Systems (ICSES
2021), held in Nepal during September 17-18, 2021. The book
focusses on the research information related to artificial
intelligence, sustainability, and expert systems applied in almost
all the areas of industries, government sectors, and educational
institutions worldwide. The main thrust of the book is to publish
the conference papers that deal with the design, implementation,
development, testing, and management of intelligent and sustainable
expert systems and also to provide both theoretical and practical
guidelines for the deployment of these systems.
This book involves a collection of selected papers presented at
International Conference on Machine Learning and Autonomous Systems
(ICMLAS 2021), held in Tamil Nadu, India, during 24-25 September
2021. It includes novel and innovative work from experts,
practitioners, scientists and decision-makers from academia and
industry. It covers selected papers in the area of emerging modern
mobile robotic systems and intelligent information systems and
autonomous systems in agriculture, health care, education, military
and industries.
This book includes the papers presented in 2nd International
Conference on Image Processing and Capsule Networks [ICIPCN 2021].
In this digital era, image processing plays a significant role in
wide range of real-time applications like sensing, automation,
health care, industries etc. Today, with many technological
advances, many state-of-the-art techniques are integrated with
image processing domain to enhance its adaptiveness, reliability,
accuracy and efficiency. With the advent of intelligent
technologies like machine learning especially deep learning, the
imaging system can make decisions more and more accurately.
Moreover, the application of deep learning will also help to
identify the hidden information in volumetric images. Nevertheless,
capsule network, a type of deep neural network, is revolutionizing
the image processing domain; it is still in a research and
development phase. In this perspective, this book includes the
state-of-the-art research works that integrate intelligent
techniques with image processing models, and also, it reports the
recent advancements in image processing techniques. Also, this book
includes the novel tools and techniques for deploying real-time
image processing applications. The chapters will briefly discuss
about the intelligent image processing technologies, which leverage
an authoritative and detailed representation by delivering an
enhanced image and video recognition and adaptive processing
mechanisms, which may clearly define the image and the family of
image processing techniques and applications that are closely
related to the humanistic way of thinking.
This book provides a broad yet detailed introduction to neural
networks and machine learning in a statistical framework. A single,
comprehensive resource for study and further research, it explores
the major popular neural network models and statistical learning
approaches with examples and exercises and allows readers to gain a
practical working understanding of the content. This updated new
edition presents recently published results and includes six new
chapters that correspond to the recent advances in computational
learning theory, sparse coding, deep learning, big data and cloud
computing. Each chapter features state-of-the-art descriptions and
significant research findings. The topics covered include: *
multilayer perceptron; * the Hopfield network; * associative memory
models;* clustering models and algorithms; * t he radial basis
function network; * recurrent neural networks; * nonnegative matrix
factorization; * independent component analysis; *probabilistic and
Bayesian networks; and * fuzzy sets and logic. Focusing on the
prominent accomplishments and their practical aspects, this book
provides academic and technical staff, as well as graduate students
and researchers with a solid foundation and comprehensive reference
on the fields of neural networks, pattern recognition, signal
processing, and machine learning.
This book gathers selected papers presented at International
Conference on Sentimental Analysis and Deep Learning (ICSADL 2022),
jointly organized by Tribhuvan University, Nepal and Prince of
Songkla University, Thailand during 16 - 17 June, 2022. The volume
discusses state-of-the-art research works on incorporating
artificial intelligence models like deep learning techniques for
intelligent sentiment analysis applications. Emotions and
sentiments are emerging as the most important human factors to
understand the prominent user-generated semantics and perceptions
from the humongous volume of user-generated data. In this scenario,
sentiment analysis emerges as a significant breakthrough
technology, which can automatically analyze the human emotions in
the data-driven applications. Sentiment analysis gains the ability
to sense the existing voluminous unstructured data and delivers a
real-time analysis to efficiently automate the business processes.
This practically-oriented, all-inclusive guide covers all the major
enabling techniques for current and next-generation cellular
communications and wireless networking systems. Technologies
covered include CDMA, OFDM, UWB, turbo and LDPC coding, smart
antennas, wireless ad hoc and sensor networks, MIMO, and cognitive
radios, providing readers with everything they need to master
wireless systems design in a single volume. Uniquely, a detailed
introduction to the properties, design, and selection of RF
subsystems and antennas is provided, giving readers a clear
overview of the whole wireless system. It is also the first
textbook to include a complete introduction to speech coders and
video coders used in wireless systems. Richly illustrated with over
400 figures, and with a unique emphasis on practical and
state-of-the-art techniques in system design, rather than on the
mathematical foundations, this book is ideal for graduate students
and researchers in wireless communications, as well as for wireless
and telecom engineers.
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