| |
| |
Click the serial number on the left to view the details of the item. |
| # |
Author | Title | Accn# | Year | Item Type | Claims |
| 1 |
Khrennikov, Andrei Y |
Open Quantum Systems in Biology, Cognitive and Social Sciences |
I12723 |
2023 |
eBook |
|
| 2 |
Pisarchik, Alexander N |
Multistability in Physical and Living Systems |
I12538 |
2022 |
Book |
|
| 3 |
Zhang, Ziye |
Complex-Valued Neural Networks Systems with Time Delay |
I12311 |
2022 |
Book |
|
| 4 |
Uncini, Aurelio |
Digital Audio Processing Fundamentals |
I12272 |
2022 |
Book |
|
| 5 |
Huang, Haiping |
Statistical Mechanics of Neural Networks |
I11949 |
2021 |
eBook |
|
| 6 |
Doboli, Simona |
Creativity and Innovation |
I11934 |
2021 |
eBook |
|
| 7 |
Hramov, Alexander E |
Wavelets in Neuroscience |
I11833 |
2021 |
eBook |
|
| 8 |
Berner, Rico |
Patterns of Synchrony in Complex Networks of Adaptively Coupled Oscillators |
I11814 |
2021 |
eBook |
|
| 9 |
Petrovici, Mihai Alexandru |
Form Versus Function: Theory and Models for Neuronal Substrates |
I10320 |
2016 |
eBook |
|
| 10 |
Treur, Jan |
Network-Oriented Modeling |
I10173 |
2016 |
eBook |
|
|
|
1.
  |
 |
| Title | Open Quantum Systems in Biology, Cognitive and Social Sciences |
| Author(s) | Khrennikov, Andrei Y |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2023. |
| Description | XXI, 371 p. 11 illus., 10 illus. in color : online resource |
| Abstract Note | This book mathematically analyzes the basic problems of biology, decision making and psychology within the framework of the theory of open quantum systems. In recent years there has been an explosion of interest in applications of quantum theory in fields beyond physics. The main areas include psychology, decision-making, economics, finance, social science as well as genetics and molecular biology. The corresponding models are referred to as quantum-like; they don???t concern any genuine physical processes in the human brain. Quantum-like models reflect the special features of information processing in biological, cognitive, and social systems which match well with the quantum formalism. This formalism gives rise to the quantum probability model (QP) which differs essentially from Kolmogorov's classical probability model. QP also serves as the basis for quantum information theory. Recently QP has been widely applied to the resolution of the basic paradoxes ofdecision making theory and to modeling experimental data stemming from cognition, psychology, economics, and finance thereby shedding light on probability fallacies and irrational behavior. In this book, the theory of quantum instruments and the quantum master equation are applied to the modeling of biological and cognitive processes, in particular, to the stability of complex biological and social systems interacting with their environment. An essential part of the book is devoted to the theory of the social laser and the Fr??hlich condensate. |
| ISBN,Price | 9783031290244 |
| Keyword(s) | 1. BIOPHYSICS
2. Cognitive science
3. EBOOK - SPRINGER
4. Mathematical Models of Cognitive Processes and Neural Networks
5. MATHEMATICS
6. Mathematics in the Humanities and Social Sciences
7. Neural networks (Computer science)??
8. QUANTUM PHYSICS
9. SOCIAL SCIENCES
|
| Item Type | eBook |
Multi-Media Links
media link description
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12723 |
|
|
On Shelf |
|
|
|
|
2.
 |
|
| Title | Multistability in Physical and Living Systems : Characterization and Applications |
| Author(s) | Pisarchik, Alexander N;Hramov, Alexander E |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XVI, 408 p. 247 illus., 144 illus. in color : online resource |
| Abstract Note | This book starts with an introduction to the basic concepts of multistability, then illustrates how multistability arises in different systems and explains the main mechanisms of multistability emergence. A special attention is given to noise which can convert a multistable deterministic system to a monostable stochastic one. Furthermore, the most important applications of multistability in different areas of science, engineering and technology are given attention throughout the book, including electronic circuits, lasers, secure communication, and human perception. The book aims to provide a first approach to multistability for readers, who are interested in understanding its fundamental concepts and applications in several fields. This book will be useful not only to researchers and engineers focusing on interdisciplinary studies, but also to graduate students and technicians. Both theoreticians and experimentalists will rely on it, in fields ranging from mathematics and laser physics to neuroscience and astronomy. The book is intended to fill a gap in the literature, to stimulate new discussions and bring some fundamental issues to a deeper level of understanding of the mechanisms underlying self-organization of matter and world complexity |
| ISBN,Price | 9783030983963 |
| Keyword(s) | 1. COMPLEX SYSTEMS
2. DYNAMICAL SYSTEMS
3. EBOOK
4. EBOOK - SPRINGER
5. Mathematical Models of Cognitive Processes and Neural Networks
6. Neural networks (Computer science)??
7. PLASMA WAVES
8. SYSTEM THEORY
9. Waves, instabilities and nonlinear plasma dynamics
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12538 |
|
|
On Shelf |
|
|
|
|
|
3.
|
|
| Title | Complex-Valued Neural Networks Systems with Time Delay : Stability Analysis and (Anti-)Synchronization Control |
| Author(s) | Zhang, Ziye;Wang, Zhen;Chen, Jian;Lin, Chong |
| Publication | Singapore, 1. Imprint: Springer
2. Springer Nature Singapore, 2022. |
| Description | XII, 229 p. 49 illus., 48 illus. in color : online resource |
| Abstract Note | This book provides up-to-date developments in the stability analysis and (anti-)synchronization control area for complex-valued neural networks systems with time delay. It brings out the characteristic systematism in them and points out further insight to solve relevant problems. It presents a comprehensive, up-to-date, and detailed treatment of dynamical behaviors including stability analysis and (anti-)synchronization control. The materials included in the book are mainly based on the recent research work carried on by the authors in this domain. The book is a useful reference for all those from senior undergraduates, graduate students, to senior researchers interested in or working with control theory, applied mathematics, system analysis and integration, automation, nonlinear science, computer and other related fields, especially those relevant scientific and technical workers in the research of complex-valued neural network systems, dynamic systems, and intelligent control theory |
| ISBN,Price | 9789811954504 |
| Keyword(s) | 1. Control and Systems Theory
2. Control engineering
3. EBOOK
4. EBOOK - SPRINGER
5. Mathematical Models of Cognitive Processes and Neural Networks
6. Neural networks (Computer science)??
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12311 |
|
|
On Shelf |
|
|
|
|
|
4.
|
|
| Title | Digital Audio Processing Fundamentals |
| Author(s) | Uncini, Aurelio |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XVI, 716 p. 533 illus., 413 illus. in color : online resource |
| Abstract Note | The book provides an accessible overview of audio signal processing, and enables readers to design and write algorithms for the analysis, synthesis, and manipulation of musical and acoustic signals for any programming language. It provides an overview of highly interdisciplinary topics developed in a simple but rigorous way, and described in a unified and formal language which focuses on determining discrete-time audio signal models. Readers can find within a self-contained volume basic topics ranging over different disciplines: mechanical acoustics, physical systems and linear and nonlinear models, with lumped and distributed parameters; described and developed with the same level of mathematical formalism, easy to understand and oriented to the development of algorithms. Topics include the fundamental concepts of acoustic mechanics and vibration; the design of filters and equalizers for sound signals, the so-called audio effects, abstract methods of sound synthesis, and finally, methods of synthesis by physical modeling |
| ISBN,Price | 9783031142284 |
| Keyword(s) | 1. ACOUSTICS
2. Computational Intelligence
3. EBOOK
4. EBOOK - SPRINGER
5. Mathematical Models of Cognitive Processes and Neural Networks
6. Neural networks (Computer science)??
7. SIGNAL PROCESSING
8. Speech and Audio Processing
9. Speech processing systems
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12272 |
|
|
On Shelf |
|
|
|
|
|
5.
|
|
| Title | Statistical Mechanics of Neural Networks |
| Author(s) | Huang, Haiping |
| Publication | Singapore, Springer Nature Singapore, 2021. |
| Description | XVIII, 296 p. 62 illus., 40 illus. in color : online resource |
| Abstract Note | This book highlights a comprehensive introduction to the fundamental statistical mechanics underneath the inner workings of neural networks. The book discusses in details important concepts and techniques including the cavity method, the mean-field theory, replica techniques, the Nishimori condition, variational methods, the dynamical mean-field theory, unsupervised learning, associative memory models, perceptron models, the chaos theory of recurrent neural networks, and eigen-spectrums of neural networks, walking new learners through the theories and must-have skillsets to understand and use neural networks. The book focuses on quantitative frameworks of neural network models where the underlying mechanisms can be precisely isolated by physics of mathematical beauty and theoretical predictions. It is a good reference for students, researchers, and practitioners in the area of neural networks |
| ISBN,Price | 9789811675706 |
| Keyword(s) | 1. ARTIFICIAL INTELLIGENCE
2. Computational Intelligence
3. EBOOK
4. EBOOK - SPRINGER
5. Mathematical Models of Cognitive Processes and Neural Networks
6. Neural networks (Computer science)??
7. STATISTICAL MECHANICS
8. STATISTICAL PHYSICS
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11949 |
|
|
On Shelf |
|
|
|
|
|
6.
|
|
| Title | Creativity and Innovation : Cognitive, Social, and Computational Approaches |
| Author(s) | Doboli, Simona;Kenworthy, Jared B;Minai, Ali A;Paulus, Paul B |
| Publication | Cham, Springer International Publishing, 2021. |
| Description | XIV, 274 p. 53 illus., 48 illus. in color : online resource |
| Abstract Note | This book focuses on the emergence of creative ideas from cognitive and social dynamics. In particular, it presents data, models, and analytical methods grounded in a network dynamics approach. It has long been hypothesized that innovation arises from a recombination of older ideas and concepts, but this has been studied primarily at an abstract level. In this book, we consider the networks underlying innovation ??? from the brain networks supporting semantic cognition to human networks such as brainstorming groups or individuals interacting through social networks ??? and relate the emergence of ideas to the structure and dynamics of these networks. Methods described include experimental studies with human participants, mathematical evaluation of novelty from group brainstorming experiments, neurodynamical modeling of conceptual combination, and multi-agent modeling of collective creativity. The main distinctive features of this book are the breadth of perspectives considered, the integration of experiments with theory, and a focus on the combinatorial emergence of ideas |
| ISBN,Price | 9783030771980 |
| Keyword(s) | 1. Applied Dynamical Systems
2. Biotechnology
3. DYNAMICS
4. EBOOK
5. EBOOK - SPRINGER
6. GRAPH THEORY
7. Mathematical Models of Cognitive Processes and Neural Networks
8. Neural networks (Computer science)??
9. NEUROPSYCHOLOGY
10. NONLINEAR THEORIES
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11934 |
|
|
On Shelf |
|
|
|
|
|
7.
|
|
| Title | Wavelets in Neuroscience |
| Author(s) | Hramov, Alexander E;Koronovskii, Alexey A;Makarov, Valeri A;Maksimenko, Vladimir A;Pavlov, Alexey N;Sitnikova, Evgenia |
| Publication | Cham, Springer International Publishing, 2021. |
| Description | XVI, 384 p. 174 illus., 69 illus. in color : online resource |
| Abstract Note | This book illustrates how modern mathematical wavelet transform techniques offer fresh insights into the complex behavior of neural systems at different levels: from the microscopic dynamics of individual cells to the macroscopic behavior of large neural networks. It also demonstrates how and where wavelet-based mathematical tools can provide an advantage over classical approaches used in neuroscience. The authors well describe single neuron and populational neural recordings. This 2nd edition discusses novel areas and significant advances resulting from experimental techniques and computational approaches developed since 2015, and includes three new topics: ??? Detection of fEPSPs in multielectrode LFPs recordings. ??? Analysis of Visual Sensory Processing in the Brain and BCI for Human Attention Control; ??? Analysis and Real-time Classification of Motor-related EEG Patterns; The book is a valuable resource for neurophysiologists and physicists familiar with nonlinear dynamical systems and data processing, as well as for graduate students specializing in these and related areas |
| ISBN,Price | 9783030759926 |
| Keyword(s) | 1. Applied Dynamical Systems
2. BIOPHYSICS
3. DYNAMICS
4. EBOOK
5. EBOOK - SPRINGER
6. GRAPH THEORY
7. Mathematical Models of Cognitive Processes and Neural Networks
8. Neural networks (Computer science)??
9. NEUROSCIENCE
10. Neurosciences
11. NONLINEAR THEORIES
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11833 |
|
|
On Shelf |
|
|
|
|
|
8.
|
|
| Title | Patterns of Synchrony in Complex Networks of Adaptively Coupled Oscillators |
| Author(s) | Berner, Rico |
| Publication | Cham, Springer International Publishing, 2021. |
| Description | XVI, 203 p. 51 illus., 44 illus. in color : online resource |
| Abstract Note | The focus of this thesis is the interplay of synchrony and adaptivity in complex networks. Synchronization is a ubiquitous phenomenon observed in different contexts in physics, chemistry, biology, neuroscience, medicine, socioeconomic systems, and engineering. Most prominently, synchronization takes place in the brain, where it is associated with cognitive capacities like learning and memory, but is also a characteristic of neurological diseases like Parkinson and epilepsy. Adaptivity is common in many networks in nature and technology, where the connectivity changes in time, i.e., the strength of the coupling is continuously adjusted depending upon the dynamic state of the system, for instance synaptic neuronal plasticity in the brain. This research contributes to a fundamental understanding of various synchronization patterns, including hierarchical multifrequency clusters, chimeras and other partial synchronization states. After a concise survey of the fundamentals of adaptive and complex dynamical networks and synaptic plasticity, in the first part of the thesis the existence and stability of cluster synchronization in globally coupled adaptive networks is discussed for simple paradigmatic phase oscillators as well as for a more realistic neuronal oscillator model with spike-timing dependent plasticity. In the second part of the thesis the interplay of adaptivity and connectivity is investigated for more complex network structures like nonlocally coupled rings, random networks, and multilayer systems. Besides presenting a plethora of novel, sometimes intriguing patterns of synchrony, the thesis makes a number of pioneering methodological advances, where rigorous mathematical proofs are given in the Appendices. These results are of interest not only from a fundamental point of view, but also with respect to challenging applications in neuroscience and technological systems |
| ISBN,Price | 9783030749385 |
| Keyword(s) | 1. COMPLEX SYSTEMS
2. DYNAMICAL SYSTEMS
3. EBOOK
4. EBOOK - SPRINGER
5. Mathematical Models of Cognitive Processes and Neural Networks
6. Neural networks (Computer science)??
7. SYSTEM THEORY
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11814 |
|
|
On Shelf |
|
|
|
|
|
9.
|
|
| Title | Form Versus Function: Theory and Models for Neuronal Substrates |
| Author(s) | Petrovici, Mihai Alexandru |
| Publication | Cham, Springer International Publishing, 2016. |
| Description | XXVI, 374 p. 150 illus., 101 illus. in color : online resource |
| Abstract Note | This thesis addresses one of the most fundamental challenges for modern science: how can the brain as a network of neurons process information, how can it create and store internal models of our world, and how can it infer conclusions from ambiguous data? The author addresses these questions with the rigorous language of mathematics and theoretical physics, an approach that requires a high degree of abstraction to transfer results of wet lab biology to formal models. The thesis starts with an in-depth description of the state-of-the-art in theoretical neuroscience, which it subsequently uses as a basis to develop several new and original ideas. Throughout the text, the author connects the form and function of neuronal networks. This is done in order to achieve functional performance of biological brains by transferring their form to synthetic electronics substrates, an approach referred to as neuromorphic computing. The obvious aspect that this transfer can never be perfect but necessarily leads to performance differences is substantiated and explored in detail. The author also introduces a novel interpretation of the firing activity of neurons. He proposes a probabilistic interpretation of this activity and shows by means of formal derivations that stochastic neurons can sample from internally stored probability distributions. This is corroborated by the author???s recent findings, which confirm that biological features like the high conductance state of networks enable this mechanism. The author goes on to show that neural sampling can be implemented on synthetic neuromorphic circuits, paving the way for future applications in machine learning and cognitive computing, for example as energy-efficient implementations of deep learning networks. The thesis offers an essential resource for newcomers to the field and an inspiration for scientists working in theoretical neuroscience and the future of computing |
| ISBN,Price | 9783319395524 |
| Keyword(s) | 1. COMPUTER SIMULATION
2. EBOOK
3. EBOOK - SPRINGER
4. Mathematical Models of Cognitive Processes and Neural Networks
5. Neural networks (Computer science)??
6. NEUROBIOLOGY
7. Neurosciences
8. Numerical and Computational Physics, Simulation
9. PHYSICS
10. Simulation and Modeling
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I10320 |
|
|
On Shelf |
|
|
|
|
|
10.
| |
| Title | Network-Oriented Modeling : Addressing Complexity of Cognitive, Affective and Social Interactions |
| Author(s) | Treur, Jan |
| Publication | Cham, Springer International Publishing, 2016. |
| Description | XVI, 499 p. 134 illus., 52 illus. in color : online resource |
| Abstract Note | This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models ??? including those for ownership of actions, fear and dreaming, the integration of emotions in joint decision-making based on empathic understanding, and evolving social networks ??? illustrate the potential of the approach. Dedicated software is available to support building models in a conceptual or graphical manner, transforming them into an executable format and performing simulation experiments. The majority of the material presented has been used and positively evaluated by undergraduate and graduate students and researchers in the cognitive, social and AI domains. Given its detailed coverage, the book is ideally suited as an introduction for graduate and undergraduate students in many different multidisciplinary fields involving cognitive, affective, social, biological, and neuroscience domains |
| ISBN,Price | 9783319452135 |
| Keyword(s) | 1. APPLICATION SOFTWARE
2. Applications of Graph Theory and Complex Networks
3. COMPLEXITY
4. COMPUTATIONAL COMPLEXITY
5. Computer Appl. in Social and Behavioral Sciences
6. Data-driven Science, Modeling and Theory Building
7. EBOOK
8. EBOOK - SPRINGER
9. ECONOPHYSICS
10. Mathematical Models of Cognitive Processes and Neural Networks
11. Neural networks (Computer science)??
12. PHYSICS
13. Sociophysics
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I10173 |
|
|
On Shelf |
|
|
|
| |