Download or read book Deep Convolutional Neural HyperSpaces and Deep Functional Analysis written by Abdourrahmane M. Atto and published by ISTE Group. This book was released on 2023-02-01 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes a transverse mathematical perspective of deep machine learning in artificial intelligence, and to do so, it develops a framework of generalized transformations, called multiserial and hyperserial decompositions, in order to unify standard and recent data representation spaces. The generalization consists of integrating expressions of several variants of convolutional neural networks and wavelet filter banks in the same analytical framework. The integrated expressions are derived recursively, from downstream to upstream layers, to show the sequence of features returned at the nodes of a network model architecture. The inspiring framework for the derivation of these expressions is that of M-band convolution filter banks. Inter-layer inter-node expressions are provided, and activation sequences of convolutional neural networks are mathematically described by suitable algebraic path representations. The topics covered address mathematical optimization, generalized functions and functional analysis, focusing on convolution integrals, probability entropy, statistical models and convolutional neural compositions.
Download or read book Convolutional Fractional Stochastic Fields and their Deep Learning written by Abdourrahmane M. Atto and published by ISTE Group. This book was released on 2023-02-01 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a stochastic environment where reality is described through samples or examples, artificial intelligence learns by penalizing weighted differential and/or integral viewpoints. The convolutional neural framework is relevant to encompass the mathematical operations performed by such an artificial intelligence. Conversely, mathematical compositions alternating convolutions and non linear operators are powerful tools for generating complex artificial realities. This book proposes a stochastic integral perspective of deep machine learning in artificial intelligence. The organization of the book is as follows. Chapter 1 introduces the basics of stochastic reasoning and the most useful properties of stochastic processes. Chapters 2 and 3 derive stochastic convoluted models for the construction, analysis and simulation of fractionally integrated fields. Chapter 4 highlights how some deep artificial neurons can disentangle the very long-range stochastic dependencies, when these neurons are parameterized to integrate spectral responses.
Download or read book Poincar Lemma on Differential Forms and Connections with ech De Rham Dolbeault Cohomologies written by Ahmed Lesfari and published by ISTE Group. This book was released on 2024-08-07 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Poincaré Lemma on Differential Forms and Connections with Čech-De Rham-Dolbeault Cohomologies deals with the connections between Čech-De Rham-Dolbeault cohomologies and the Dolbeault- Grothendieck lemma. It begins by discussing one-parameter groups of diffeomorphisms or flow, Lie derivative and interior products, as well as Cartan’s formula and the Poincaré lemma on differential forms. Throughout the book, we study sheaves, Čech cohomology and De Rham cohomology, and present some of their most basic properties. We also explore the Mayer-Vietoris sequence by demonstrating its use when calculating the cohomology group of the sphere. We introduce the Künneth formula (and as an application) and compute the cohomology of the torus. The final sections of the book study the delta bar-Poincaré lemma – as well as the Dolbeault-Grothendieck lemma and its consequences – while also proving the delta bar-Poincaré lemma in one variable, the Grothendieck Poincaré lemma, and the Dolbeault’s theorem when establishing the isomorphism between Dolbeault and Čech cohomology. Some results related to the connections, curvature and first Chern class of line bundles are also given. The text is enriched by concrete examples, along with exercises and their solutions.
Download or read book Machine Learning Advanced Dynamic Omics Data Analysis for Precision Medicine written by Tao Zeng and published by Frontiers Media SA. This book was released on 2020-03-30 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book ASM Metals Reference Book 3rd Edition written by Michael Bauccio and published by ASM International. This book was released on 1993-01-01 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reference book makes it easy for anyone involved in materials selection, or in the design and manufacture of metallic structural components to quickly screen materials for a particular application. Information on practically all ferrous and nonferrous metals including powder metals is presented in tabular form for easy review and comparison between different materials. Included are chemical compositions, physical and mechanical properties, manufacturing processes, applications, pertinent specifications and standards, and test methods. Contents Overview: Glossary of metallurgical terms Selection of structural materials (specifications and standards, life cycle and failure modes, materials properties and design, and properties and applications) Physical data on the elements and alloys Testing and inspection Chemical composition and processing characteristics
Download or read book Metric Structures for Riemannian and Non Riemannian Spaces written by Mikhail Gromov and published by Springer Science & Business Media. This book was released on 2007-06-25 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an English translation of the famous "Green Book" by Lafontaine and Pansu (1979). It has been enriched and expanded with new material to reflect recent progress. Additionally, four appendices, by Gromov on Levy's inequality, by Pansu on "quasiconvex" domains, by Katz on systoles of Riemannian manifolds, and by Semmes overviewing analysis on metric spaces with measures, as well as an extensive bibliography and index round out this unique and beautiful book.
Download or read book Cybernetics Cognition and Machine Learning Applications written by Vinit Kumar Gunjan and published by Springer. This book was released on 2020-05-30 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a collection of selected papers presented at the International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2019), which was held in Goa, India, on 16–17 August 2019. It covers the latest research trends and advances in the areas of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber-physical systems, and cybernetics.
Download or read book The Adaptive Web written by Peter Brusilovski and published by Springer Science & Business Media. This book was released on 2007-04-24 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: This state-of-the-art survey provides a systematic overview of the ideas and techniques of the adaptive Web and serves as a central source of information for researchers, practitioners, and students. The volume constitutes a comprehensive and carefully planned collection of chapters that map out the most important areas of the adaptive Web, each solicited from the experts and leaders in the field.
Download or read book Comparative Vertebrate Neuroanatomy written by Ann B. Butler and published by John Wiley & Sons. This book was released on 2005-09-02 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comparative Vertebrate Neuroanatomy Evolution and Adaptation Second Edition Ann B. Butler and William Hodos The Second Edition of this landmark text presents a broad survey of comparative vertebrate neuroanatomy at the introductory level, representing a unique contribution to the field of evolutionary neurobiology. It has been extensively revised and updated, with substantially improved figures and diagrams that are used generously throughout the text. Through analysis of the variation in brain structure and function between major groups of vertebrates, readers can gain insight into the evolutionary history of the nervous system. The text is divided into three sections: * Introduction to evolution and variation, including a survey of cell structure, embryological development, and anatomical organization of the central nervous system; phylogeny and diversity of brain structures; and an overview of various theories of brain evolution * Systematic, comprehensive survey of comparative neuroanatomy across all major groups of vertebrates * Overview of vertebrate brain evolution, which integrates the complete text, highlights diversity and common themes, broadens perspective by a comparison with brain structure and evolution of invertebrate brains, and considers recent data and theories of the evolutionary origin of the brain in the earliest vertebrates, including a recently proposed model of the origin of the brain in the earliest vertebrates that has received strong support from newly discovered fossil evidence Ample material drawn from the latest research has been integrated into the text and highlighted in special feature boxes, including recent views on homology, cranial nerve organization and evolution, the relatively large and elaborate brains of birds in correlation with their complex cognitive abilities, and the current debate on forebrain evolution across reptiles, birds, and mammals. Comparative Vertebrate Neuroanatomy is geared to upper-level undergraduate and graduate students in neuroanatomy, but anyone interested in the anatomy of the nervous system and how it corresponds to the way that animals function in the world will find this text fascinating.
Download or read book Intelligent Interactive Multimedia Systems for e Healthcare Applications written by Shaveta Malik and published by CRC Press. This book was released on 2022-11-30 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume explores how the merging of interactive multimedia with artificial intelligence has created new and advanced tools in healthcare. It looks at how the latest technologies (artificial intelligence, deep learning, machine learning, big data, IoT, smart device, etc.) help to manage health data, diagnose health issues, monitor treatment, predict pandemic diseases, and more. The book covers several important applications of multimedia in healthcare, including for data visualization purposes, for computer vision for elder healthcare monitoring, for detection of lung nodules, for management systems using machine learning techniques, and for fusion applications in medical image processing. The chapter authors discuss using data mining and machine learning techniques for COVID-19 diagnosis and prediction, in detecting knee osteoarthritis using texture descriptor algorithms, in applying algorithms in fetal ECG enhancement using blockchain for wearable internet of things in healthcare, and more. A chapter also reviews how doctors can make good use of genomics and genetic data through advanced technology. The book concludes with discussions of open issues, challenges, and future research directions for using intelligent interactive multimedia in healthcare. Key features: Provides an in-depth understanding of emerging technologies and integration of artificial intelligence, deep learning, big data, IoT in healthcare Details specific applications for the use of AI, big data, and IoT in healthcare Discusses how AI technology can help in formulating protective measures for COVID-19 and other diseases Includes case studies Intelligent Interactive Multimedia Systems for e-Healthcare Applications will be valuable to undergraduate and graduate students planning their careers in either industry or research and to software engineers for using multimedia with artificial intelligence, deep learning, big data, and IoT for healthcare applications.
Download or read book Continuous Selections of Multivalued Mappings written by Dusan Repovs and published by Springer Science & Business Media. This book was released on 1998-09-30 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consists of three relatively independent parts--theory, results, and applications. The first part is directed toward advanced math students who wish to get familiar with the foundations of the theory. The second part surveys the existing results on continuous selections of multivalued mappings. It is intended for specialists in the area and for those who have mastered the first part. The third part collects examples of applications of continuous selections that have played a key role in the corresponding areas of mathematics. It is written for researchers in general and geometric topology, functional and convex analysis, approximation theory and fixed-point theory, differential inclusions, and mathematical economics. Annotation copyrighted by Book News, Inc., Portland, OR
Download or read book Big Data written by Kuan-Ching Li and published by CRC Press. This book was released on 2015-02-23 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages.Pre
Download or read book The Porous Medium Equation written by Juan Luis Vazquez and published by Clarendon Press. This book was released on 2006-10-26 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Heat Equation is one of the three classical linear partial differential equations of second order that form the basis of any elementary introduction to the area of PDEs, and only recently has it come to be fairly well understood. In this monograph, aimed at research students and academics in mathematics and engineering, as well as engineering specialists, Professor Vazquez provides a systematic and comprehensive presentation of the mathematical theory of the nonlinear heat equation usually called the Porous Medium Equation (PME). This equation appears in a number of physical applications, such as to describe processes involving fluid flow, heat transfer or diffusion. Other applications have been proposed in mathematical biology, lubrication, boundary layer theory, and other fields. Each chapter contains a detailed introduction and is supplied with a section of notes, providing comments, historical notes or recommended reading, and exercises for the reader.
Download or read book Pharmako AI written by K. Allado-McDowell and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book collects essays, stories, and poems ... [the author] wrote with OpenAI's GPT-3 language model, a neural net that generates text sequences"--Page xi.
Download or read book Cybernetics Cognition and Machine Learning Applications written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on 2021-03-30 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the original, peer reviewed research articles from the 2nd International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2020), held in August, 2020 at Goa, India. It covers the latest research trends or developments in areas of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber physical systems and cybernetics.
Download or read book Advanced Algorithms and Data Structures written by Marcello La Rocca and published by Simon and Schuster. This book was released on 2021-08-10 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. Summary As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Can you improve the speed and efficiency of your applications without investing in new hardware? Well, yes, you can: Innovations in algorithms and data structures have led to huge advances in application performance. Pick up this book to discover a collection of advanced algorithms that will make you a more effective developer. About the book Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You’ll discover cutting-edge approaches to a variety of tricky scenarios. You’ll even learn to design your own data structures for projects that require a custom solution. What's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms About the reader For intermediate programmers. About the author Marcello La Rocca is a research scientist and a full-stack engineer. His focus is on optimization algorithms, genetic algorithms, machine learning, and quantum computing. Table of Contents 1 Introducing data structures PART 1 IMPROVING OVER BASIC DATA STRUCTURES 2 Improving priority queues: d-way heaps 3 Treaps: Using randomization to balance binary search trees 4 Bloom filters: Reducing the memory for tracking content 5 Disjoint sets: Sub-linear time processing 6 Trie, radix trie: Efficient string search 7 Use case: LRU cache PART 2 MULTIDEMENSIONAL QUERIES 8 Nearest neighbors search 9 K-d trees: Multidimensional data indexing 10 Similarity Search Trees: Approximate nearest neighbors search for image retrieval 11 Applications of nearest neighbor search 12 Clustering 13 Parallel clustering: MapReduce and canopy clustering PART 3 PLANAR GRAPHS AND MINIMUM CROSSING NUMBER 14 An introduction to graphs: Finding paths of minimum distance 15 Graph embeddings and planarity: Drawing graphs with minimal edge intersections 16 Gradient descent: Optimization problems (not just) on graphs 17 Simulated annealing: Optimization beyond local minima 18 Genetic algorithms: Biologically inspired, fast-converging optimization
Download or read book Applications of Computational Intelligence in Biology written by Tomasz G. Smolinski and published by Springer. This book was released on 2010-10-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence (CI) has been a tremendously active area of - search for the past decade or so. There are many successful applications of CI in many sub elds of biology, including bioinformatics, computational - nomics, protein structure prediction, or neuronal systems modeling and an- ysis. However, there still are many open problems in biology that are in d- perate need of advanced and e cient computational methodologies to deal with tremendous amounts of data that those problems are plagued by. - fortunately, biology researchers are very often unaware of the abundance of computational techniques that they could put to use to help them analyze and understand the data underlying their research inquiries. On the other hand, computational intelligence practitioners are often unfamiliar with the part- ular problems that their new, state-of-the-art algorithms could be successfully applied for. The separation between the two worlds is partially caused by the use of di erent languages in these two spheres of science, but also by the relatively small number of publications devoted solely to the purpose of fac- itating the exchange of new computational algorithms and methodologies on one hand, and the needs of the biology realm on the other. The purpose of this book is to provide a medium for such an exchange of expertise and concerns. In order to achieve the goal, we have solicited cont- butions from both computational intelligence as well as biology researchers.
