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    Mendel, Jerry M.
    Uncertain Rule-Based Fuzzy Systems [Electronic resource] : introduction and New Directions, 2nd Edition / / Jerry M. Mendel ; . - 2nd ed. 2017. - [S. l. : s. n.]. - XXII, 684 p. 215 illus., 192 illus. in color. - ISBN 9783319513706
    Зміст:

Рубрики: Electrical engineering.
   Computational intelligence.
   Artificial intelligence.
   Neural networks (Computer science) .
   Communications Engineering, Networks.
   Computational Intelligence.
   Artificial Intelligence.
   Mathematical Models of Cognitive Processes and Neural Networks.
Анотація: The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material. Presents fully updated material on new breakthroughs in human-inspired rule-based techniques for handling real-world uncertainties; Allows those already familiar with type-1 fuzzy sets and systems to rapidly come up to speed to type-2 fuzzy sets and systems; Features complete classroom material including end-of-chapter exercises, a solutions manual, and three case studies -- forecasting of time series to knowledge mining from surveys and PID control.
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    Lubashevsky, Ihor.
    Physics of the Human Mind [Electronic resource] / Ihor. Lubashevsky ; . - 1st ed. 2017. - [S. l. : s. n.]. - XIV, 380 p. 83 illus., 41 illus. in color. - ISBN 9783319517063
    Зміст:

Рубрики: Sociophysics.
   Econophysics.
   Neural networks (Computer science) .
   Cognitive psychology.
   Philosophy of mind.
   Physics.
   Data-driven Science, Modeling and Theory Building.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Cognitive Psychology.
   Philosophy of Mind.
   Mathematical Methods in Physics.
Анотація: This book tackles the challenging question which mathematical formalisms and possibly new physical notions should be developed for quantitatively describing human cognition and behavior, in addition to the ones already developed in the physical and cognitive sciences. Indeed, physics is widely used in modeling social systems, where, in particular, new branches of science such as sociophysics and econophysics have arisen. However, many if not most characteristic features of humans like willingness, emotions, memory, future prediction, and moral norms, to name but a few, are not yet properly reflected in the paradigms of physical thought and theory. The choice of a relevant formalism for modeling mental phenomena requires the comprehension of the general philosophical questions related to the mind-body problem. Plausible answers to these questions are investigated and reviewed, notions and concepts to be used or to be taken into account are developed and some challenging questions are posed as open problems. This text addresses theoretical physicists and neuroscientists modeling any systems and processes where human factors play a crucial role, philosophers interested in applying philosophical concepts to the construction of mathematical models, and the mathematically oriented psychologists and sociologists, whose research is fundamentally related to modeling mental processes.
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    da Silva, Silva, Ivan Nunes.
    Artificial Neural Networks [Electronic resource] : a Practical Course / / Silva, Ivan Nunes. da Silva, Hernane Spatti, Danilo. [et al.] ; . - 1st ed. 2017. - [S. l. : s. n.]. - XX, 307 p. 203 illus., 13 illus. in color. - ISBN 9783319431628
    Зміст:

Рубрики: Electrical engineering.
   Computational intelligence.
   Neural networks (Computer science) .
   Data mining.
   Pattern recognition.
   Communications Engineering, Networks.
   Computational Intelligence.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Data Mining and Knowledge Discovery.
   Pattern Recognition.
Анотація: This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.
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Hernane Spatti, Danilo.; Andrade Flauzino, Rogerio.; Liboni, Luisa Helena Bartocci.; dos Reis Alves, Silas Franco.; da Silva, Ivan Nunes. \.\
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    Cognitive Neuroscience of Memory Consolidation [Electronic resource] / ed.: Axmacher, Nikolai., Rasch, Björn. - 1st ed. 2017. - [S. l. : s. n.]. - XV, 417 p. 52 illus., 43 illus. in color. - ISBN 9783319450667
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Рубрики: Cognitive psychology.
   Neurosciences.
   Biomedical engineering.
   Neurobiology.
   Neural networks (Computer science) .
   Cognitive Psychology.
   Neurosciences.
   Biomedical Engineering and Bioengineering.
   Neurobiology.
   Mathematical Models of Cognitive Processes and Neural Networks.
Анотація: This edited volume provides an overview the state-of-the-art in the field of cognitive neuroscience of memory consolidation. In a number of sections, the editors collect contributions of leading researchers. The topical focus lies on current issues of interest such as memory consolidation including working and long-term memory. In particular, the role of sleep in relation to memory consolidation will be addressed. The target audience primarily comprises research experts in the field of cognitive neuroscience but the book may also be beneficial for graduate students.
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Axmacher, Nikolai. \ed.\; Rasch, Björn. \ed.\
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    Florescu, Dorian.
    Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits [Electronic resource] / Dorian. Florescu ; . - 1st ed. 2017. - [S. l. : s. n.]. - XIV, 139 p. 42 illus., 27 illus. in color. - ISBN 9783319570815
    Зміст:

Рубрики: Signal processing.
   Image processing.
   Speech processing systems.
   Neural networks (Computer science) .
   Neurosciences.
   System theory.
   Electronic circuits.
   Signal, Image and Speech Processing.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Neurosciences.
   Systems Theory, Control.
   Circuits and Systems.
Анотація: This work is motivated by the ongoing open question of how information in the outside world is represented and processed by the brain. Consequently, several novel methods are developed. A new mathematical formulation is proposed for the encoding and decoding of analog signals using integrate-and-fire neuron models. Based on this formulation, a novel algorithm, significantly faster than the state-of-the-art method, is proposed for reconstructing the input of the neuron. Two new identification methods are proposed for neural circuits comprising a filter in series with a spiking neuron model. These methods reduce the number of assumptions made by the state-of-the-art identification framework, allowing for a wider range of models of sensory processing circuits to be inferred directly from input-output observations. A third contribution is an algorithm that computes the spike time sequence generated by an integrate-and-fire neuron model in response to the output of a linear filter, given the input of the filter encoded with the same neuron model.
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    Modeling Cellular Systems [Electronic resource] / ed.: Graw, Frederik., Matthäus, Franziska., Pahle, Jürgen. - 1st ed. 2017. - [S. l. : s. n.]. - XI, 161 p. 35 illus., 29 illus. in color. - ISBN 9783319458335
    Зміст:

Рубрики: Biomedical engineering.
   Biomathematics.
   Systems biology.
   Biological systems.
   Neural networks (Computer science) .
   Biomedical Engineering and Bioengineering.
   Physiological, Cellular and Medical Topics.
   Systems Biology.
   Systems Biology.
   Mathematical Models of Cognitive Processes and Neural Networks.
Анотація: This contributed volume comprises research articles and reviews on topics connected to the mathematical modeling of cellular systems. These contributions cover signaling pathways, stochastic effects, cell motility and mechanics, pattern formation processes, as well as multi-scale approaches. All authors attended the workshop on "Modeling Cellular Systems" which took place in Heidelberg in October 2014. The target audience primarily comprises researchers and experts in the field, but the book may also be beneficial for graduate students.
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Graw, Frederik. \ed.\; Matthäus, Franziska. \ed.\; Pahle, Jürgen. \ed.\
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    Börgers, Christoph.
    An Introduction to Modeling Neuronal Dynamics [Electronic resource] / Christoph. Börgers ; . - 1st ed. 2017. - [S. l. : s. n.]. - XIII, 457 p. 356 illus., 186 illus. in color. - ISBN 9783319511719
    Зміст:

Рубрики: Neural networks (Computer science) .
   Biomathematics.
   Neurosciences.
   Statistical physics.
   Vibration.
   Dynamical systems.
   Dynamics.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Mathematical and Computational Biology.
   Neurosciences.
   Statistical Physics and Dynamical Systems.
   Vibration, Dynamical Systems, Control.
Анотація: This book is intended as a text for a one-semester course on Mathematical and Computational Neuroscience for upper-level undergraduate and beginning graduate students of mathematics, the natural sciences, engineering, or computer science. An undergraduate introduction to differential equations is more than enough mathematical background. Only a slim, high school-level background in physics is assumed, and none in biology. Topics include models of individual nerve cells and their dynamics, models of networks of neurons coupled by synapses and gap junctions, origins and functions of population rhythms in neuronal networks, and models of synaptic plasticity. An extensive online collection of Matlab programs generating the figures accompanies the book. .
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    Neuman, Yair.
    Mathematical Structures of Natural Intelligence [Electronic resource] / Yair. Neuman ; . - 1st ed. 2017. - [S. l. : s. n.]. - XVII, 173 p. 39 illus., 6 illus. in color. - ISBN 9783319682464
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Рубрики: Category theory (Mathematics).
   Homological algebra.
   Neural networks (Computer science) .
   Algebraic topology.
   Category Theory, Homological Algebra.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Algebraic Topology.
Анотація: This book uncovers mathematical structures underlying natural intelligence and applies category theory as a modeling language for understanding human cognition, giving readers new insights into the nature of human thought. In this context, the book explores various topics and questions, such as the human representation of the number system, why our counting ability is different from that which is evident among non-human organisms, and why the idea of zero is so difficult to grasp. The book is organized into three parts: the first introduces the general reason for studying general structures underlying the human mind; the second part introduces category theory as a modeling language and use it for exposing the deep and fascinating structures underlying human cognition; and the third applies the general principles and ideas of the first two parts to reaching a better understanding of challenging aspects of the human mind such as our understanding of the number system, the metaphorical nature of our thinking and the logic of our unconscious dynamics. About the Author: Yair Neuman is a Full Professor at Ben-Gurion University. He holds a BA in Psychology (Major) and Philosophy (Minor) and a PhD in Cognition (Hebrew University, 1999), and his expertise is in studying complex cognitive, social, and symbolic systems from a unique interdisciplinary approach. Professor Neuman has published numerous papers and five academic books and has been a visiting scholar or professor at MIT, the University of Toronto, the University of Oxford, and the Weizmann Institute of Science. Beyond his purely academic work, he has developed state-of-the-art algorithms for social and cognitive computing, such as those he developed for the IARPA metaphor project (ADAMA group).
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    Advances in Neural Networks - ISNN 2017 [Electronic resource] : 14th International Symposium, ISNN 2017, Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21–26, 2017, Proceedings, Part II / / ed.: Cong, Fengyu., Leung, Andrew., Wei, Qinglai. - 1st ed. 2017. - [S. l. : s. n.]. - XXII, 595 p. 251 illus. - ISBN 9783319590813
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Рубрики: Pattern recognition.
   Artificial intelligence.
   Computer science—Mathematics.
   Neural networks (Computer science) .
   Algorithms.
   Computer security.
   Pattern Recognition.
   Artificial Intelligence.
   Mathematics of Computing.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Algorithm Analysis and Problem Complexity.
   Systems and Data Security.
Анотація: This book constitutes the refereed proceedings of the 14th International Symposium on Neural Networks, ISNN 2017, held in Sapporo, Hakodate, and Muroran, Hokkaido, Japan, in June 2017. The 135 revised full papers presented in this two-volume set were carefully reviewed and selected from 259 submissions. The papers cover topics like perception, emotion and development, action and motor control, attractor and associative memory, neurodynamics, complex systems, and chaos.
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Cong, Fengyu. \ed.\; Leung, Andrew. \ed.\; Wei, Qinglai. \ed.\
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10.

    Computational Neurology and Psychiatry [Electronic resource] / ed.: Érdi, Péter., Sen Bhattacharya, Basabdatta., Cochran, Amy L. - 1st ed. 2017. - [S. l. : s. n.]. - VI, 448 p. 157 illus., 119 illus. in color. - ISBN 9783319499598
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Рубрики: Computational intelligence.
   Computer simulation.
   Neurosciences.
   Neural networks (Computer science) .
   Computational Intelligence.
   Simulation and Modeling.
   Neurosciences.
   Mathematical Models of Cognitive Processes and Neural Networks.
Анотація: This book presents the latest research in computational methods for modeling and simulating brain disorders. In particular, it shows how mathematical models can be used to study the relationship between a given disorder and the specific brain structure associated with that disorder. It also describes the emerging field of computational psychiatry, including the study of pathological behavior due to impaired functional connectivity, pathophysiological activity, and/or aberrant decision-making. Further, it discusses the data analysis techniques that will be required to analyze the increasing amount of data being generated about the brain. Lastly, the book offers some tips on the application of computational models in the field of quantitative systems pharmacology. Mainly written for computational scientists eager to discover new application fields for their model, this book also benefits neurologists and psychiatrists wanting to learn about new methods.
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Érdi, Péter. \ed.\; Sen Bhattacharya, Basabdatta. \ed.\; Cochran, Amy L. \ed.\
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11.

    Iatan, Iuliana F.
    Issues in the Use of Neural Networks in Information Retrieval [Electronic resource] / Iuliana F. Iatan ; . - 1st ed. 2017. - [S. l. : s. n.]. - XIX, 199 p. 88 illus., 44 illus. in color. - ISBN 9783319438719
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Рубрики: Computational intelligence.
   Artificial intelligence.
   Neural networks (Computer science) .
   Pattern recognition.
   Computational Intelligence.
   Artificial Intelligence.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Pattern Recognition.
Анотація: This book highlights the ability of neural networks (NNs) to be excellent pattern matchers and their importance in information retrieval (IR), which is based on index term matching. The book defines a new NN-based method for learning image similarity and describes how to use fuzzy Gaussian neural networks to predict personality. It introduces the fuzzy Clifford Gaussian network, and two concurrent neural models: (1) concurrent fuzzy nonlinear perceptron modules, and (2) concurrent fuzzy Gaussian neural network modules. Furthermore, it explains the design of a new model of fuzzy nonlinear perceptron based on alpha level sets and describes a recurrent fuzzy neural network model with a learning algorithm based on the improved particle swarm optimization method.
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Iatan, Iuliana F. \.\
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12.

    Advances in Memristors, Memristive Devices and Systems [Electronic resource] / ed.: Vaidyanathan, Sundarapandian., Volos, Christos. - 1st ed. 2017. - [S. l. : s. n.]. - XII, 511 p. 294 illus., 229 illus. in color. - ISBN 9783319517247
    Зміст:

Рубрики: Computational intelligence.
   Electronic circuits.
   Electronics.
   Microelectronics.
   Neural networks (Computer science) .
   Computational Intelligence.
   Circuits and Systems.
   Electronics and Microelectronics, Instrumentation.
   Mathematical Models of Cognitive Processes and Neural Networks.
Анотація: This book reports on the latest advances in and applications of memristors, memristive devices and systems. It gathers 20 contributed chapters by subject experts, including pioneers in the field such as Leon Chua (UC Berkeley, USA) and R.S. Williams (HP Labs, USA), who are specialized in the various topics addressed in this book, and covers broad areas of memristors and memristive devices such as: memristor emulators, oscillators, chaotic and hyperchaotic memristive systems, control of memristive systems, memristor-based min-max circuits, canonic memristors, memristive-based neuromorphic applications, implementation of memristor-based chaotic oscillators, inverse memristors, linear memristor devices, delayed memristive systems, flux-controlled memristive emulators, etc. Throughout the book, special emphasis is given to papers offering practical solutions and design, modeling, and implementation insights to address current research problems in memristors, memristive devices and systems. As such, it offers a valuable reference book on memristors and memristive devices for graduate students and researchers with a basic knowledge of electrical and control systems engineering.
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Vaidyanathan, Sundarapandian. \ed.\; Volos, Christos. \ed.\
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13.

    Anticipation and Medicine [Electronic resource] / ed. Nadin, Mihai. - 1st ed. 2017. - [S. l. : s. n.]. - IX, 363 p. 49 illus., 31 illus. in color. - ISBN 9783319451428
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Рубрики: Computational intelligence.
   Neural networks (Computer science) .
   Artificial intelligence.
   Computational Intelligence.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Artificial Intelligence.
Анотація: In this book, practicing physicians and experts in anticipation present arguments for a new understanding of medicine. Their contributions make it clear that medicine is the decisive test for anticipation. The reader is presented with a provocative hypothesis: If medicine will align itself with the anticipatory condition of life, it can prompt the most important revolution in our time. To this end, all stakeholders—medical practitioners, patients, scientists, and technology developers—will have to engage in the conversation. The book makes the case for the transition from expensive, and only marginally effective, reactive treatment through “spare parts” (joint replacements, organ transplants) and reliance on pharmaceuticals (antibiotics, opiates) to anticipation-informed healthcare. Readers will understand why the current premise of treating various behavioral conditions (attention deficit disorder, hyperactivity, schizophrenia) through drugs has to be re-evaluated from the perspective of anticipation. In the manner practiced today, medicine generates dependence and long-lasting damage to those it is paid to help. As we better understand the nature of the living, the proactive view of healthcare, within which the science and art of healing fuse, becomes a social and political mandate.
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Nadin, Mihai. \ed.\
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14.

    Emergent Complexity from Nonlinearity, in Physics, Engineering and the Life Sciences [Electronic resource] : proceedings of the XXIII International Conference on Nonlinear Dynamics of Electronic Systems, Como, Italy, 7-11 September 2015 / / ed.: Mantica, Giorgio., Stoop, Ruedi., Stramaglia, Sebastiano. - 1st ed. 2017. - [S. l. : s. n.]. - XXV, 222 p. 113 illus., 86 illus. in color. - ISBN 9783319478104
Рубрики: Statistical physics.
   Dynamical systems.
   Electronics.
   Microelectronics.
   Systems biology.
   Neural networks (Computer science) .
   Biochemistry.
   Complex Systems.
   Electronics and Microelectronics, Instrumentation.
   Systems Biology.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Biochemistry, general.
   Statistical Physics and Dynamical Systems.
Анотація: This book collects contributions to the XXIII international conference “Nonlinear dynamics of electronic systems”. Topics range from non-linearity in electronic circuits to synchronisation effects in complex networks to biological systems, neural dynamics and the complex organisation of the brain. Resting on a solid mathematical basis, these investigations address highly interdisciplinary problems in physics, engineering, biology and biochemistry.
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Mantica, Giorgio. \ed.\; Stoop, Ruedi. \ed.\; Stramaglia, Sebastiano. \ed.\
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15.

    Piotrowski, David.
    Morphogenesis of the Sign [Electronic resource] / David. Piotrowski ; . - 1st ed. 2017. - [S. l. : s. n.]. - XII, 299 p. 50 illus. - ISBN 9783319553252
Рубрики: Computational linguistics.
   Neural networks (Computer science) .
   Neurobiology.
   Natural language processing (Computer science).
   Epistemology.
   Computational Linguistics.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Neurobiology.
   Natural Language Processing (NLP).
   Epistemology.
Анотація: This book develops a morphodynamical approach to linguistic and sign structures as an integrated response to multilevel and interrelated problems in semiolinguistic research. More broadly, the content is linked to the realities of living speech through a connection (via the concept of diacriticity) with the Merleau-Pontian phenomenology, and beyond the formal determinations of a semiolinguistic system and its calculus. Such problems are mainly epistemological (concerning the nature and legitimate scope of semiolinguistic knowledge), empirical (concerning the observational device and the data’s composition), and theoretical (regarding the choice of a conceptual and formalized explicative frame). With regard to theory, the book introduces a morphodynamical architecture of linguistic signs and operations as a suitable mathematization of Saussurean theory. The Husserlian phenomenological signification of this formal apparatus is then established, and, from an empirical standpoint, its compatibility with neurobiological experimental results is discussed.
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16.

    Petitot, Jean.
    Elements of Neurogeometry [Electronic resource] : functional Architectures of Vision / / Jean. Petitot ; . - 1st ed. 2017. - [S. l. : s. n.]. - XV, 379 p. 257 illus., 186 illus. in color. - ISBN 9783319655918
    Зміст:

Рубрики: Biomathematics.
   Neural networks (Computer science) .
   Geometry.
   Mathematical and Computational Biology.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Geometry.
Анотація: This book describes several mathematical models of the primary visual cortex, referring them to a vast ensemble of experimental data and putting forward an original geometrical model for its functional architecture, that is, the highly specific organization of its neural connections. The book spells out the geometrical algorithms implemented by this functional architecture, or put another way, the “neurogeometry” immanent in visual perception. Focusing on the neural origins of our spatial representations, it demonstrates three things: firstly, the way the visual neurons filter the optical signal is closely related to a wavelet analysis; secondly, the contact structure of the 1-jets of the curves in the plane (the retinal plane here) is implemented by the cortical functional architecture; and lastly, the visual algorithms for integrating contours from what may be rather incomplete sensory data can be modelled by the sub-Riemannian geometry associated with this contact structure. As such, it provides readers with the first systematic interpretation of a number of important neurophysiological observations in a well-defined mathematical framework. The book’s neuromathematical exploration appeals to graduate students and researchers in integrative-functional-cognitive neuroscience with a good mathematical background, as well as those in applied mathematics with an interest in neurophysiology.
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Petitot, Jean. \.\
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17.

    Language in Complexity [Electronic resource] : the Emerging Meaning / / ed.: La Mantia, Francesco., Licata, Ignazio., Perconti, Pietro. - 1st ed. 2017. - [S. l. : s. n.]. - XXVI, 199 p. 18 illus., 12 illus. in color. - ISBN 9783319294834
    Зміст:

Рубрики: Computational complexity.
   Computational linguistics.
   Natural language processing (Computer science).
   Neural networks (Computer science) .
   Neurosciences.
   Complexity.
   Computational Linguistics.
   Natural Language Processing (NLP).
   Mathematical Models of Cognitive Processes and Neural Networks.
   Neurosciences.
Анотація: This contributed volume explores the achievements gained and the remaining puzzling questions by applying dynamical systems theory to the linguistic inquiry. In particular, the book is divided into three parts, each one addressing one of the following topics: 1) Facing complexity in the right way: mathematics and complexity 2) Complexity and theory of language 3) From empirical observation to formal models: investigation of specific linguistic phenomena, like enunciation, deixis, or the meaning of the metaphorical phrases The application of complexity theory to describe cognitive phenomena is a recent and very promising trend in cognitive science. At the time when dynamical approaches triggered a paradigm shift in cognitive science some decade ago, the major topic of research were the challenges imposed by classical computational approaches dealing with the explanation of cognitive phenomena like consciousness, decision making and language. The target audience primarily comprises researchers and experts in the field but the book may also be beneficial for graduate and post-graduate students who want to enter the field.
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La Mantia, Francesco. \ed.\; Licata, Ignazio. \ed.\; Perconti, Pietro. \ed.\
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18.

    Pinna, Simone.
    Extended Cognition and the Dynamics of Algorithmic Skills [Electronic resource] / Simone. Pinna ; . - 1st ed. 2017. - [S. l. : s. n.]. - XXVII, 122 p. 5 illus. - ISBN 9783319518411
    Зміст:

Рубрики: Philosophy of mind.
   Computers.
   Neural networks (Computer science) .
   Cognitive psychology.
   Philosophy of Mind.
   Computation by Abstract Devices.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Cognitive Psychology.
Анотація: This book describes a novel methodology for studying algorithmic skills, intended as cognitive activities related to rule-based symbolic transformation, and argues that some human computational abilities may be interpreted and analyzed as genuine examples of extended cognition. It shows that the performance of these abilities relies not only on innate neurocognitive systems or language-related skills, but also on external tools and general agent–environment interactions. Further, it asserts that a low-level analysis, based on a set of core neurocognitive systems linking numbers and language, is not sufficient to explain some specific forms of high-level numerical skills, like those involved in algorithm execution. To this end, it reports on the design of a cognitive architecture for modeling all the relevant features involved in the execution of algorithmic strategies, including external tools, such as paper and pencils. The first part of the book discusses the philosophical premises for endorsing and justifying a position in philosophy of mind that links a modified form of computationalism with some recent theoretical and scientific developments, like those introduced by the so-called dynamical approach to cognition. The second part is dedicated to the description of a Turing-machine-inspired cognitive architecture, expressly designed to formalize all kinds of algorithmic strategies.
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Pinna, Simone. \.\
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19.

    Kong, Xiangyu.
    Principal Component Analysis Networks and Algorithms [Electronic resource] / Xiangyu. Kong, Hu, Changhua., Duan, Zhansheng. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XXII, 323 p. 86 illus., 41 illus. in color. - ISBN 9789811029158
    Зміст:

Рубрики: Computational intelligence.
   Pattern recognition.
   Neural networks (Computer science) .
   Statistics .
   Algorithms.
   Signal processing.
   Image processing.
   Speech processing systems.
   Computational Intelligence.
   Pattern Recognition.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Statistical Theory and Methods.
   Algorithm Analysis and Problem Complexity.
   Signal, Image and Speech Processing.
Анотація: This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.
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Hu, Changhua.; Duan, Zhansheng.; Kong, Xiangyu. \.\
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20.

    Advances in Neural Networks - ISNN 2017 [Electronic resource] : 14th International Symposium, ISNN 2017, Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21–26, 2017, Proceedings, Part I / / ed.: Cong, Fengyu., Leung, Andrew., Wei, Qinglai. - 1st ed. 2017. - [S. l. : s. n.]. - XXII, 583 p. 238 illus. - ISBN 9783319590721
    Зміст:

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