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Author : Axel Sandvig,Matteo Caleo,Ioanna Sandvig
Publisher : Frontiers Media SA
Page : 171 pages
File Size : 49,7 Mb
Release : 2023-02-03
Category : Science
ISBN : 9782832513248
Author : Sharon Chiang,Vikram Rao,Gregory Worrell,Maxime O. Baud
Publisher : Frontiers Media SA
Page : 207 pages
File Size : 51,7 Mb
Release : 2022-03-31
Category : Medical
ISBN : 9782889748723
Author : Nergis Tomen,J. Michael Herrmann,Udo Ernst
Publisher : Springer
Page : 287 pages
File Size : 52,6 Mb
Release : 2019-07-23
Category : Medical
ISBN : 9783030209650
This book offers a timely overview of theories and methods developed by an authoritative group of researchers to understand the link between criticality and brain functioning. Cortical information processing in particular and brain function in general rely heavily on the collective dynamics of neurons and networks distributed over many brain areas. A key concept for characterizing and understanding brain dynamics is the idea that networks operate near a critical state, which offers several potential benefits for computation and information processing. However, there is still a large gap between research on criticality and understanding brain function. For example, cortical networks are not homogeneous but highly structured, they are not in a state of spontaneous activation but strongly driven by changing external stimuli, and they process information with respect to behavioral goals. So far the questions relating to how critical dynamics may support computation in this complex setting, and whether they can outperform other information processing schemes remain open. Based on the workshop “Dynamical Network States, Criticality and Cortical Function", held in March 2017 at the Hanse Institute for Advanced Studies (HWK) in Delmenhorst, Germany, the book provides readers with extensive information on these topics, as well as tools and ideas to answer the above-mentioned questions. It is meant for physicists, computational and systems neuroscientists, and biologists.
Author : Simone Bassis,Anna Esposito,Francesco Carlo Morabito
Publisher : Springer
Page : 402 pages
File Size : 50,7 Mb
Release : 2015-06-05
Category : Technology & Engineering
ISBN : 9783319181646
This book collects research works that exploit neural networks and machine learning techniques from a multidisciplinary perspective. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and bio-inspired memristor-based networks. Providing insights into the latest research interest from a pool of international experts coming from different research fields, the volume becomes valuable to all those with any interest in a holistic approach to implement believable, autonomous, adaptive and context-aware Information Communication Technologies.
Author : Marcel van Gerven,Sander Bohte
Publisher : Frontiers Media SA
Page : 220 pages
File Size : 42,6 Mb
Release : 2018-02-01
Category : Electronic
ISBN : 9782889454013
Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.
Author : Ranjodh Singh Dhaliwal,Théo LePage-Richer,Lucy Suchman
Publisher : U of Minnesota Press
Page : 158 pages
File Size : 42,7 Mb
Release : 2024-04-09
Category : Social Science
ISBN : 9781452970493
A critical examination of the figure of the neural network as it mediates neuroscientific and computational discourses and technical practices Neural Networks proposes to reconstruct situated practices, social histories, mediating techniques, and ontological assumptions that inform the computational project of the same name. If so-called machine learning comprises a statistical approach to pattern extraction, then neural networks can be defined as a biologically inspired model that relies on probabilistically weighted neuron-like units to identify such patterns. Far from signaling the ultimate convergence of human and machine intelligence, however, neural networks highlight the technologization of neurophysiology that characterizes virtually all strands of neuroscientific and AI research of the past century. Taking this traffic as its starting point, this volume explores how cognition came to be constructed as essentially computational in nature, to the point of underwriting a technologized view of human biology, psychology, and sociability, and how countermovements provide resources for thinking otherwise.
Author : Krešimir Josic,Jonathan Rubin,Manuel Matias,Ranulfo Romo
Publisher : Springer Science & Business Media
Page : 311 pages
File Size : 44,6 Mb
Release : 2009-08-22
Category : Medical
ISBN : 9781441903891
Recent experimental research advances have led to increasingly detailed descriptions of how networks of interacting neurons process information. With these developments, it has become clear that dynamic network behaviors underlie information processing, and that the observed activity patterns cannot be fully explained by simple concepts such as synchrony and phase locking. These new insights raise significant challenges and offer exciting opportunities for experimental and theoretical neuroscientists. Coherent Behavior in Neuronal Networks features a review of recent research in this area from some of the world’s foremost experts on systems neuroscience. The book presents novel methodologies and interdisciplinary perspectives, and will serve as an invaluable resource to the research community. Highlights include the results of interdisciplinary collaborations and approaches as well as topics, such as the interplay of intrinsic and synaptic dynamics in producing coherent neuronal network activity and the roles of globally coherent rhythms and oscillations in the coordination of distributed processing, that are of significant research interest but have been underrepresented in the review literature. With its cutting-edge mathematical, statistical, and computational techniques, this volume will be of interest to all researchers and students in the field of systems neuroscience.
Author : Dave J. Hayes,Georg Northoff,Andrew J. Greenshaw
Publisher : Frontiers Media SA
Page : 183 pages
File Size : 41,5 Mb
Release : 2016-05-18
Category : Electronic book
ISBN : 9782889198368
Affective brain circuits underpin our moods and emotions. Appetitive and aversive stimuli from our exteroceptive and interoceptive worlds play a key role in the activity of these circuits, but we still do not know precisely how to characterize these so-called reward-related and aversion-related systems. Moreover, we do we yet understand how they interact anatomically or functionally. The aim of the current project was to gather some translational evidence to help clarify the role of such circuits. A multi-dimensional problem in its own right, the book contains 14 works from authors exploring these questions at many levels, from the cellular to the cognitive-behavioural, and from both experimental and conceptual viewpoints. The editorial which introduces the book provides brief summaries of each perspective (Hayes, Northoff, Greenshaw, 2015). While questions of how to accurately define affect- and emotion-related concepts at the psychological level are far from answered, here we have attempted to provide some insight into the brain-based underpinnings of such processes. The near future will undoubtedly involve making new inroads and will require the joint efforts of behavioural, brain-based, and philosophical perspectives to do so.
Author : Hava T. Siegelmann
Publisher : Springer Science & Business Media
Page : 193 pages
File Size : 49,5 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461207078
The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. On a mathematical level, the treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.
Author : Daniel S. Levine,Manuel Aparicio IV
Publisher : Psychology Press
Page : 526 pages
File Size : 49,9 Mb
Release : 2013-04-15
Category : Psychology
ISBN : 9781134771615
The second published collection based on a conference sponsored by the Metroplex Institute for Neural Dynamics -- the first is Motivation, Emotion, and Goal Direction in Neural Networks (LEA, 1992) -- this book addresses the controversy between symbolicist artificial intelligence and neural network theory. A particular issue is how well neural networks -- well established for statistical pattern matching -- can perform the higher cognitive functions that are more often associated with symbolic approaches. This controversy has a long history, but recently erupted with arguments against the abilities of renewed neural network developments. More broadly than other attempts, the diverse contributions presented here not only address the theory and implementation of artificial neural networks for higher cognitive functions, but also critique the history of assumed epistemologies -- both neural networks and AI -- and include several neurobiological studies of human cognition as a real system to guide the further development of artificial ones. Organized into four major sections, this volume: * outlines the history of the AI/neural network controversy, the strengths and weaknesses of both approaches, and shows the various capabilities such as generalization and discreetness as being along a broad but common continuum; * introduces several explicit, theoretical structures demonstrating the functional equivalences of neurocomputing with the staple objects of computer science and AI, such as sets and graphs; * shows variants on these types of networks that are applied in a variety of spheres, including reasoning from a geographic database, legal decision making, story comprehension, and performing arithmetic operations; * discusses knowledge representation process in living organisms, including evidence from experimental psychology, behavioral neurobiology, and electroencephalographic responses to sensory stimuli.
Author : Francisco Sandoval,Alberto Prieto,Joan Cabestany,Manuel Graña
Publisher : Springer
Page : 1167 pages
File Size : 49,9 Mb
Release : 2007-09-21
Category : Computers
ISBN : 9783540730071
This book constitutes the refereed proceedings of the 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, held in San Sebastián, Spain in June 2007. Coverage includes theoretical concepts and neurocomputational formulations, evolutionary and genetic algorithms, data analysis, signal processing, robotics and planning motor control, as well as neural networks and other machine learning methods in cancer research.
Author : Ignacio Rojas,Gonzalo Joya,Andreu Catala
Publisher : Springer
Page : 763 pages
File Size : 41,7 Mb
Release : 2017-06-04
Category : Computers
ISBN : 9783319591476
This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, held in Cadiz, Spain, in June 2017. The 126 revised full papers presented in this double volume were carefully reviewed and selected from 199 submissions. The papers are organized in topical sections on Bio-inspired Computing; E-Health and Computational Biology; Human Computer Interaction; Image and Signal Processing; Mathematics for Neural Networks; Self-organizing Networks; Spiking Neurons; Artificial Neural Networks in Industry ANNI'17; Computational Intelligence Tools and Techniques for Biomedical Applications; Assistive Rehabilitation Technology; Computational Intelligence Methods for Time Series; Machine Learning Applied to Vision and Robotics; Human Activity Recognition for Health and Well-Being Applications; Software Testing and Intelligent Systems; Real World Applications of BCI Systems; Machine Learning in Imbalanced Domains; Surveillance and Rescue Systems and Algorithms for Unmanned Aerial Vehicles; End-User Development for Social Robotics; Artificial Intelligence and Games; and Supervised, Non-Supervised, Reinforcement and Statistical Algorithms.
Author : Vivienne Sze,Yu-Hsin Chen,Tien-Ju Yang,Joel S. Emer
Publisher : Morgan & Claypool Publishers
Page : 354 pages
File Size : 45,9 Mb
Release : 2020-06-24
Category : Computers
ISBN : 9781681738321
This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of the DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as a formalization and organization of key concepts from contemporary works that provides insights that may spark new ideas.
Author : Ignacio Rojas,Gonzalo Joya,Andreu Catala
Publisher : Springer
Page : 761 pages
File Size : 40,8 Mb
Release : 2017-06-04
Category : Computers
ISBN : 9783319591537
This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, held in Cadiz, Spain, in June 2017. The 126 revised full papers presented in this double volume were carefully reviewed and selected from 199 submissions. The papers are organized in topical sections on Bio-inspired Computing; E-Health and Computational Biology; Human Computer Interaction; Image and Signal Processing; Mathematics for Neural Networks; Self-organizing Networks; Spiking Neurons; Artificial Neural Networks in Industry ANNI'17; Computational Intelligence Tools and Techniques for Biomedical Applications; Assistive Rehabilitation Technology; Computational Intelligence Methods for Time Series; Machine Learning Applied to Vision and Robotics; Human Activity Recognition for Health and Well-Being Applications; Software Testing and Intelligent Systems; Real World Applications of BCI Systems; Machine Learning in Imbalanced Domains; Surveillance and Rescue Systems and Algorithms for Unmanned Aerial Vehicles; End-User Development for Social Robotics; Artificial Intelligence and Games; and Supervised, Non-Supervised, Reinforcement and Statistical Algorithms.
Author : Cesare Alippi,Marios M. Polycarpou,Christos Panayiotou,Georgios Ellinas
Publisher : Springer
Page : 1030 pages
File Size : 43,8 Mb
Release : 2009-09-16
Category : Computers
ISBN : 9783642042744
This volume is part of the two-volume proceedings of the 19th International Conf- ence on Artificial Neural Networks (ICANN 2009), which was held in Cyprus during September 14–17, 2009. The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational Intel- gence Society. This series of conferences has been held annually since 1991 in various European countries and covers the field of neurocomputing, learning systems and related areas. Artificial neural networks provide an information-processing structure inspired by biological nervous systems. They consist of a large number of highly interconnected processing elements, with the capability of learning by example. The field of artificial neural networks has evolved significantly in the last two decades, with active partici- tion from diverse fields, such as engineering, computer science, mathematics, artificial intelligence, system theory, biology, operations research, and neuroscience. Artificial neural networks have been widely applied for pattern recognition, control, optimization, image processing, classification, signal processing, etc.