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Author: Pijush Samui Publisher: Academic Press ISBN: 0128113197 Category : Technology & Engineering Languages : en Pages : 660
Book Description
Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. - Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more - Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing - Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods
Author: Pijush Samui Publisher: Academic Press ISBN: 0128113197 Category : Technology & Engineering Languages : en Pages : 660
Book Description
Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. - Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more - Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing - Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods
Author: David L. Waltz Publisher: SIAM ISBN: 9780898713572 Category : Computers Languages : en Pages : 220
Book Description
The volume begins with processing in biological organisms, moves through interactions between processing in biology and computer science, and ends with massively parallel computing. It contains articles by scientists exploring the modeling of biological systems on computers and computer designers interested in exploiting massive numbers of computing elements in parallel.
Author: Kia Nobre Publisher: ISBN: 0199563454 Category : Medical Languages : en Pages : 478
Book Description
Our ability to attend selectively to our surroundings - taking notice of the things that matter, and ignoring those that don't - is crucial if we are to negotiate the world around us in an efficient manner. Several aspects of the temporal dimension turn out to be critical in determining how we can put together and select the events that are important to us as they themselves unfold over time. For example, we often miss events that happen while we are occupied perceiving or responding to another stimulus. On the other hand, temporal regularity between events can also greatly improve our perception. In addition, our perception of the passage of time itself can also be distorted as while we are performing actions or paying attention to different aspects of the environment. Surprisingly, this fascinating and fundamental interplay between ' attention' and 'time' has been relatively neglected in the psychology and neuroscience literatures until very recently. Attention & Time is the first book to address this foundational topic, bringing together several intriguing and hitherto fragmented findings into a compelling and cohesive field of enquiry. The book contains thirty-one critical-review chapters from internationally recognised experts in the field, carefully organised into three stand-alone, yet extensively cross-referenced, themed sections. Each section focuses on distinct ways in which attention and time influence one another. These sections, each encompassing a range of methodologies from classical cognitive psychology to single-cell neurophysiology, provide functionally unifying frameworks to help guide the reader through the many various experimental and theoretical approaches adopted. Section 1 considers variations of attention across time, and explores how attentional allocation is limited by very short or very long intervals of time. Section 2 describes several types of temporal illusion, illustrating how attention can modulate the perception of the passage of time itself. "A watched pot never boils" and, conversely, "time flies when you're having fun" nicely capture the experimental observation that the degree of attention allocated to stimulus timing contributes to its subjective duration. Finally, Section 3 examines how attention can be directed in time, to predictable or expected moments in time, so as to optimise behaviour. Bringing conceptually discrete, yet functionally related, fields of temporal attention research together within a single volume, this book provides a comprehensive overview that will be of value to the interested novice in cognitive neuroscience, whilst also inspiring experts in the field to make, perhaps previously overlooked, links with their own field of research.
Author: John A. Hertz Publisher: CRC Press ISBN: 0429968213 Category : Science Languages : en Pages : 352
Book Description
Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.
Author: Peter Riederer Publisher: Springer Nature ISBN: 303062059X Category : Medical Languages : en Pages : 4652
Book Description
This book provides a reference guide describing the current status of medication in all major psychiatric and neurological indications, together with comparisons of pharmacological treatment strategies in clinical settings in Europe, USA, Japan and China. In addition, it highlights herbal medicine as used in China and Japan, as well as complementary medicine and nutritional aspects. This novel approach offers international readers a global approach in a single dedicated publication and is also a valuable resource for anyone interested in comparing treatments for psychiatric disorders in three different cultural areas. There are three volumes devoted to Basic Principles and General Aspects, offering a general overview of psychopharmacotherapy (Vol. 1); Classes, Drugs and Special Aspects covering the role of psychotropic drugs in the field of psychiatry and neurology (Vol. 2) and Applied Psychopharmacotherapy focusing on applied psychopharmacotherapy (Vol. 3). These books are invaluable to psychiatrists, neurologists, neuroscientists, medical practitioners and clinical psychologists.
Author: Britt Glatzeder Publisher: Springer Science & Business Media ISBN: 3642031293 Category : Psychology Languages : en Pages : 405
Book Description
What is Thinking? – Trying to Define an Equally Fascinating and Elusive Phenomenon Human thinking is probably the most complex phenomenon that evolution has come up with until now. There exists a broad spectrum of definitions, from subs- ing almost all processes of cognition to limiting it to language-based, sometimes even only to formalizable reasoning processes. We work with a “medium sized” definition according to which thinking encompasses all operations by which cog- tive agents link mental content in order to gain new insights or perspectives. Mental content is, thus, a prerequisite for and the substrate on which thinking operations are executed. The largely unconscious acts of perceptual object stabilization, ca- gorization, emotional evaluation – and retrieving all the above from memory inscriptions – are the processes by which mental content is generated, and are, therefore, seen as prerequisites for thinking operations. In terms of a differentia specifica, the notion of “thinking” is seen as narrower than the notion of “cognition” and as wider than the notion of “reasoning”. Thinking is, thus, seen as a subset of cognition processes; and reasoning processes are seen as a subset of thinking. Besides reasoning, the notion of thinking includes also nonexplicit, intuitive, and associative processes of linking mental content. According to this definition, thinking is not dependant on language, i. e. also many animals and certainly all mammals show early forms of thinking.
Author: Anupam Shukla Publisher: Springer Science & Business Media ISBN: 3642143431 Category : Computers Languages : en Pages : 467
Book Description
Soft Computing today is a very vast field whose extent is beyond measure. This book offers a well structured presentation of the basic concepts of Artificial Neural Networks, Fuzzy Inference Systems and Evolutionary Algorithms.
Author: Robert Kozma Publisher: Academic Press ISBN: 0323958168 Category : Computers Languages : en Pages : 398
Book Description
Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present 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 possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. - Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN - Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making - Edited by high-level academics and researchers in intelligent systems and neural networks - Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks
Author: Wojciech Samek Publisher: Springer Nature ISBN: 3030289540 Category : Computers Languages : en Pages : 435
Book Description
The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Author: Pijush Samui
Author: Pijush Samui
Author: David L. Waltz
Author: Kia Nobre
Author: John A. Hertz
Author: Peter Riederer
Author: Britt Glatzeder
Author: Anupam Shukla
Author: Robert Kozma
Author: Di Wu
Author: Wojciech Samek