kishan mehrotra elements of artificial neural networks

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Akira Hirose Complex-Valued Neural Networks. Advances and Applications

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and superconducting waves. This fact is a critical advantage in practical applications in diverse fields of engineering, where signals are routinely analyzed and processed in time/space, frequency, and phase domains. Complex-Valued Neural Networks: Advances and Applications covers cutting-edge topics and applications surrounding this timely subject. Demonstrating advanced theories with a wide range of applications, including communication systems, image processing systems, and brain-computer interfaces, this text offers comprehensive coverage of: Conventional complex-valued neural networks Quaternionic neural networks Clifford-algebraic neural networks Presented by international experts in the field, Complex-Valued Neural Networks: Advances and Applications is ideal for advanced-level computational intelligence theorists, electromagnetic theorists, and mathematicians interested in computational intelligence, artificial intelligence, machine learning theories, and algorithms.

10192.06 рублей

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Manjubala Bisi Artificial Neural Network Applications for Software Reliability Prediction

Artificial neural network (ANN) has proven to be a universal approximator for any non-linear continuous function with arbitrary accuracy. This book presents how to apply ANN to measure various software reliability indicators: number of failures in a given time, time between successive failures, fault-prone modules and development efforts. The application of machine learning algorithm i.e. artificial neural networks application in software reliability prediction during testing phase as well as early phases of software development process is presented as well. Applications of artificial neural network for the above purposes are discussed with experimental results in this book so that practitioners can easily use ANN models for predicting software reliability indicators.

14622.12 рублей

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Hojjat Adeli Computational Intelligence. Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: Covers all the aspects of fuzzy, neural and evolutionary approaches with worked out examples, MATLAB® exercises and applications in each chapter Presents the synergies of technologies of computational intelligence such as evolutionary fuzzy neural fuzzy and evolutionary neural systems Considers real world problems in the domain of systems modelling, control and optimization Contains a foreword written by Lotfi Zadeh Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing is an ideal text for final year undergraduate, postgraduate and research students in electrical, control, computer, industrial and manufacturing engineering.

10872.33 рублей

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Derong Liu Fundamentals of Computational Intelligence. Neural Networks, Fuzzy Systems, and Evolutionary Computation

Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.

8997.79 рублей

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Antonios Alexandridis K. Wavelet Neural Networks. With Applications in Financial Engineering, Chaos, and Classification

A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by providing in-depth coverage of both model selection and variable significance testing. Featuring an accessible approach with introductory coverage of the basic principles of wavelet analysis, Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification also includes: • Methods that can be easily implemented or adapted by researchers, academics, and professionals in identification and modeling for complex nonlinear systems and artificial intelligence • Multiple examples and thoroughly explained procedures with numerous applications ranging from financial modeling and financial engineering, time series prediction and construction of confidence and prediction intervals, and classification and chaotic time series prediction • An extensive introduction to neural networks that begins with regression models and builds to more complex frameworks • Coverage of both the variable selection algorithm and the model selection algorithm for wavelet networks in addition to methods for constructing confidence and prediction intervals Ideal as a textbook for MBA and graduate-level courses in applied neural network modeling, artificial intelligence, advanced data analysis, time series, and forecasting in financial engineering, the book is also useful as a supplement for courses in informatics, identification and modeling for complex nonlinear systems, and computational finance. In addition, the book serves as a valuable reference for researchers and practitioners in the fields of mathematical modeling, engineering, artificial intelligence, decision science, neural networks, and finance and economics.

7722.96 рублей

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Guanrong Chen Fundamentals of Complex Networks. Models, Structures and Dynamics

Complex networks such as the Internet, WWW, transportation networks, power grids, biological neural networks, and scientific cooperation networks of all kinds provide challenges for future technological development. • The first systematic presentation of dynamical evolving networks, with many up-to-date applications and homework projects to enhance study • The authors are all very active and well-known in the rapidly evolving field of complex networks • Complex networks are becoming an increasingly important area of research • Presented in a logical, constructive style, from basic through to complex, examining algorithms, through to construct networks and research challenges of the future

9372.7 рублей

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Akbar Rahbar G. Quality of Service in Optical Packet Switched Networks

This book is a comprehensive study on OPS networks, its architectures, and developed techniques for improving its quality of switching and managing quality of service. The book includes: Introduction to OPS networks, OOFDM networks, GMPLS-enabled optical networks, QoS in OPS networks Hybrid contention avoidance/resolution schemes in both long-haul and metro optical networks Hybrid optical switching schemes

9672.91 рублей

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Navjot Kaur Neural Stem Cell Assays

Neural stem cells offer a valuable model system for delineating the cellular and developmental processes in normal and diseased states of the central nervous system. In particular, neural stem cells have huge potential in regenerative medicine, owing to their expansion capability in culture and the ability to differentiate into multiple sub-neural lineages. Neural Stem Cell Assays provides a detailed and comprehensive review of the basic methods for neural stem cell cultures. Including an overview of progress in the field over the past decade, Neural Stem Cell Assays is a one-stop reference for consistent methods and reliable tools that span the entire assay work flow, from isolation or generation of neural stem cells to characterization, manipulation and final application of neural stem cells in disease paradigms such as Parkinson's disease, multiple sclerosis and amyotrophic lateral sclerosis. An excellent source of information for academic, pharmaceutical and biotechnology researchers who are new to the neural stem cell field, Neural Stem Cell Assays is an invaluable to experienced users who wish to integrate newly developed tools and technologies into their workflow. The book also covers important course material for students at the undergraduate and graduate level who are learning the basics of neural stem cell cultures, and differentiation to sub-neural lineages.

11618.58 рублей

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Indra Gunawan Fundamentals of Reliability Engineering. Applications in Multistage Interconnection Networks

This book presents fundamentals of reliability engineering with its applications in evaluating reliability of multistage interconnection networks. In the first part of the book, it introduces the concept of reliability engineering, elements of probability theory, probability distributions, availability and data analysis. The second part of the book provides an overview of parallel/distributed computing, network design considerations, and more. The book covers a comprehensive reliability engineering methods and its practical aspects in the interconnection network systems. Students, engineers, researchers, managers will find this book as a valuable reference source.

11801.33 рублей

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Lorenzo Beatriz Advanced Wireless Networks. Cognitive, Cooperative & Opportunistic 4G Technology

With 40% new material the new edition of Advanced Wireless Networks provides a comprehensive representation of the key issues in 4G wireless networks. Focussing on cognitive, cooperative and opportunistic paradigms to provide further increase in network efficiency, the book explores and addresses issues in wireless internet, mobile cellular and WLAN, as well as sensor, ad hoc, bio-inspired, active and cognitive networks. It examines the problem of cross-layer optimisation and network information theory as well as adaptability and reconfigurability in wireless networks. This book is an integral description of future wireless networks and the interconnection between their elements. The information is presented in a logical order within each chapter making it ideal for all levels of reader including researchers involved in modelling and analysis of future networks as well as engineers working in the area. Each chapter starts with introductory material and gradually includes more sophisticated models and mathematical tools concluding with a comprehensive list of references. Fully updated throughout with five new chapters on Opportunistic Communications; Relaying and Mesh Networks; Topology Control; Network Optimization; and Cognitive Radio Resource Management Unifies the latest research on cognitive, cooperative and opportunistic paradigms in wireless communications Provides efficient analytical tools for network analysis Discusses security issues, an essential element of working with wireless networks Supports advanced university and training courses in the field Companion website containing extra appendix on Queuing theory

14330.18 рублей

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Cirrincione Giansalvo Neural-Based Orthogonal Data Fitting. The EXIN Neural Networks

The presentation of a novel theory in orthogonal regression The literature about neural-based algorithms is often dedicated to principal component analysis (PCA) and considers minor component analysis (MCA) a mere consequence. Breaking the mold, Neural-Based Orthogonal Data Fitting is the first book to start with the MCA problem and arrive at important conclusions about the PCA problem. The book proposes several neural networks, all endowed with a complete theory that not only explains their behavior, but also compares them with the existing neural and traditional algorithms. EXIN neurons, which are of the authors' invention, are introduced, explained, and analyzed. Further, it studies the algorithms as a differential geometry problem, a dynamic problem, a stochastic problem, and a numerical problem. It demonstrates the novel aspects of its main theory, including its applications in computer vision and linear system identification. The book shows both the derivation of the TLS EXIN from the MCA EXIN and the original derivation, as well as: Shows TLS problems and gives a sketch of their history and applications Presents MCA EXIN and compares it with the other existing approaches Introduces the TLS EXIN neuron and the SCG and BFGS acceleration techniques and compares them with TLS GAO Outlines the GeTLS EXIN theory for generalizing and unifying the regression problems Establishes the GeMCA theory, starting with the identification of GeTLS EXIN as a generalization eigenvalue problem In dealing with mathematical and numerical aspects of EXIN neurons, the book is mainly theoretical. All the algorithms, however, have been used in analyzing real-time problems and show accurate solutions. Neural-Based Orthogonal Data Fitting is useful for statisticians, applied mathematics experts, and engineers.

8425.69 рублей

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Christopher Shaw A. Neural Dynamics of Neurological Disease

The emerging understanding of age-related neurological disorders suggests that notions of a single causal gene/toxin being responsible is likely incorrect. Neurological disorders probably arise due to a unique intersection of multiple genetic and toxic factors, combined with additional contributions of age, stage of development, immune system actions, and more. This perspective leads to the view that rather than reflecting only one pathway to end-state disease, each is a spectrum disorder, and every individual case is therefore unique. Neural Dynamics of Neurological Disease argues for a fundamental rethinking of what we think we know about neurological disorders, how they arise and progress, and, crucially, what might be done to «cure» them. It first introduces the concept of neural dynamics of neurological disease, then examines various diseases and gives examples of the interplay of elements such as neural systems, cell types, and biochemical pathways that can contribute to disease. The concluding chapters point the way to how the emerging notion of neurological disease as a dynamic process may lead to more successful treatment options. Providing a cross-disciplinary approach to understanding the origin and progression of neurological disease, Neural Dynamics of Neurological Disease is a timely and valuable resource for neuroscientists, researchers, and clinicians.

9744.05 рублей

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Luonan Chen Biomolecular Networks. Methods and Applications in Systems Biology

Alternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the important need for a new set of computational tools to reveal essential biological mechanisms from a systems biology approach. Readers will get comprehensive coverage of analyzing biomolecular networks in cellular systems based on available experimental data with an emphasis on the aspects of network, system, integration, and engineering. Each topic is treated in depth with specific biological problems and novel computational methods: GENE NETWORKS—Transcriptional regulation; reconstruction of gene regulatory networks; and inference of transcriptional regulatory networks PROTEIN INTERACTION NETWORKS—Prediction of protein-protein interactions; topological structure of biomolecular networks; alignment of biomolecular networks; and network-based prediction of protein function METABOLIC NETWORKS AND SIGNALING NETWORKS—Analysis, reconstruction, and applications of metabolic networks; modeling and inference of signaling networks; and other topics and new trends In addition to theoretical results and methods, many computational software tools are referenced and available from the authors' Web sites. Biomolecular Networks is an indispensable reference for researchers and graduate students in bioinformatics, computational biology, systems biology, computer science, and applied mathematics.

10047.81 рублей

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Noble Wilford John Bayesian Networks. An Introduction

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest.

8425.69 рублей

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Ermenegildo Zegna ELEMENTS OF MAN TALENT Парфюмерная вода ELEMENTS OF MAN TALENT Парфюмерная вода

Для талантливого мужчины, который делится своим вдохновением с окружающим миром. В древесно-цитрусовой композиции Elements of Man Talent искусно переплетаются освежающая нота юзу с харизматичным и пряным сочетанием нот черного чая, сычуаньского перца и кедра.

11284 рублей

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Ermenegildo Zegna ELEMENTS OF MAN INTEGRITY Парфюмерная вода ELEMENTS OF MAN INTEGRITY Парфюмерная вода

Аромат честного и открытого мужчины, на которого всегда можно положиться. В основе фужерно-пряной композиции Elements of Man Integrity заложены зеленые ноты мускатного шалфея и герани, смолистая нота кедра в сочетании гурманского шлейфа из бобов тонка.

11284 рублей

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Paolo Santi Mobility Models for Next Generation Wireless Networks. Ad Hoc, Vehicular and Mesh Networks

Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task. It also: Provides up-to-date coverage of mobility models for next generation wireless networks Offers an in-depth discussion of the most representative mobility models for major next generation wireless network application scenarios, including WLAN/mesh networks, vehicular networks, wireless sensor networks, and opportunistic networks Demonstrates the practices for designing effective protocol/applications for next generation wireless networks Includes case studies showcasing the importance of properly understanding fundamental mobility model properties in wireless network performance evaluation

10192.06 рублей

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Printio Elements of harmony

Футболка Wearcraft Premium — цвет: БЕЛЫЙ, пол: ЖЕН.

892 рублей

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A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by providing in-depth coverage of both model selection and variable significance testing. Featuring an accessible approach with introductory coverage of the basic principles of wavelet analysis, Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification also includes: • Methods that can be easily implemented or adapted by researchers, academics, and professionals in identification and modeling for complex nonlinear systems and artificial intelligence • Multiple examples and thoroughly explained procedures with numerous applications ranging from financial modeling and financial engineering, time series prediction and construction of confidence and prediction intervals, and classification and chaotic time series prediction • An extensive introduction to neural networks that begins with regression models and builds to more complex frameworks • Coverage of both the variable selection algorithm and the model selection algorithm for wavelet networks in addition to methods for constructing confidence and prediction intervals Ideal as a textbook for MBA and graduate-level courses in applied neural network modeling, artificial intelligence, advanced data analysis, time series, and forecasting in financial engineering, the book is also useful as a supplement for courses in informatics, identification and modeling for complex nonlinear systems, and computational finance. In addition, the book serves as a valuable reference for researchers and practitioners in the fields of mathematical modeling, engineering, artificial intelligence, decision science, neural networks, and finance and economics.

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