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Author | Title | Accn# | Year | Item Type | Claims |
| 1 |
Awojoyogbe, Bamidele O |
Digital Molecular Magnetic Resonance Imaging |
I13129 |
2024 |
eBook |
|
| 2 |
Gros, Claudius |
Complex and Adaptive Dynamical Systems |
I13034 |
2024 |
eBook |
|
| 3 |
Conti, Claudio |
Quantum Machine Learning |
I12944 |
2024 |
eBook |
|
| 4 |
Khrennikov, Andrei Y |
Open Quantum Systems in Biology, Cognitive and Social Sciences |
I12723 |
2023 |
eBook |
|
| 5 |
Pisarchik, Alexander N |
Multistability in Physical and Living Systems |
I12538 |
2022 |
Book |
|
| 6 |
Zhang, Ziye |
Complex-Valued Neural Networks Systems with Time Delay |
I12311 |
2022 |
Book |
|
| 7 |
Uncini, Aurelio |
Digital Audio Processing Fundamentals |
I12272 |
2022 |
Book |
|
| 8 |
Huang, Haiping |
Statistical Mechanics of Neural Networks |
I11949 |
2021 |
eBook |
|
| 9 |
Doboli, Simona |
Creativity and Innovation |
I11934 |
2021 |
eBook |
|
| 10 |
Hramov, Alexander E |
Wavelets in Neuroscience |
I11833 |
2021 |
eBook |
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2.
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| Title | Complex and Adaptive Dynamical Systems : A Comprehensive Introduction |
| Author(s) | Gros, Claudius |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2024. |
| Description | XV, 461 p. 167 illus., 145 illus. in color : online resource |
| Abstract Note | This textbook offers a comprehensive introduction to the concepts underpinning our modern understanding of complex and emergent behavior. Mathematical methods necessary for the discussion are introduced and explained on the run. All derivations are presented step-by-step. This new fifth edition has been fully revised and includes a new chapter, a range of new sections, figures and exercises. The Solution chapter has been reorganized for clarity. The core aspects of modern complex system sciences are presented in the first chapters, covering the foundations of network- and dynamical system theory, with a particular focus on scale-free networks and tipping phenomena. The notion of deterministic chaos is treated together with bifurcation theory and the intricacies of time delays. Modern information theoretical principles are discussed in further chapters, together with the notion of self-organized criticality, synchronization phenomena, and a game-theoretical treatment of the tragedy of the commons. The dynamical systems view of modern machine learning is presented in a new chapter. Chapters include exercises and suggestions for further reading. The textbook is suitable for graduate and advanced undergraduate students. The prerequisites are the basic mathematical tools of courses in natural sciences, computer science or engineering |
| ISBN,Price | 9783031550768 |
| Keyword(s) | 1. Applied Dynamical Systems
2. COMPLEX SYSTEMS
3. DYNAMICAL SYSTEMS
4. DYNAMICS
5. EBOOK
6. EBOOK - SPRINGER
7. GRAPH THEORY
8. Mathematical Models of Cognitive Processes and Neural Networks
9. Neural networks (Computer science)??
10. NONLINEAR THEORIES
11. Stochastic Networks
12. STOCHASTIC PROCESSES
13. 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 |
| I13034 |
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On Shelf |
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3.
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| Title | Quantum Machine Learning : Thinking and Exploration in Neural Network Models for Quantum Science and Quantum Computing |
| Author(s) | Conti, Claudio |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2024. |
| Description | XXIII, 378 p. 109 illus., 66 illus. in color : online resource |
| Abstract Note | This book presents a new way of thinking about quantum mechanics and machine learning by merging the two. Quantum mechanics and machine learning may seem theoretically disparate, but their link becomes clear through the density matrix operator which can be readily approximated by neural network models, permitting a formulation of quantum physics in which physical observables can be computed via neural networks. As well as demonstrating the natural affinity of quantum physics and machine learning, this viewpoint opens rich possibilities in terms of computation, efficient hardware, and scalability. One can also obtain trainable models to optimize applications and fine-tune theories, such as approximation of the ground state in many body systems, and boosting quantum circuits??? performance. The book begins with the introduction of programming tools and basic concepts of machine learning, with necessary background material from quantum mechanics and quantum information also provided. This enables the basic building blocks, neural network models for vacuum states, to be introduced. The highlights that follow include: non-classical state representations, with squeezers and beam splitters used to implement the primary layers for quantum computing; boson sampling with neural network models; an overview of available quantum computing platforms, their models, and their programming; and neural network models as a variational ansatz for many-body Hamiltonian ground states with applications to Ising machines and solitons. The book emphasizes coding, with many open source examples in Python and TensorFlow, while MATLAB and Mathematica routines clarify and validate proofs. This book is essential reading for graduate students and researchers who want to develop both the requisite physics and coding knowledge to understand the rich interplay of quantum mechanics and machine learning |
| ISBN,Price | 9783031442261 |
| Keyword(s) | 1. Computational Physics and Simulations
2. COMPUTER SIMULATION
3. EBOOK
4. EBOOK - SPRINGER
5. MACHINE LEARNING
6. Mathematical Models of Cognitive Processes and Neural Networks
7. MATHEMATICAL PHYSICS
8. Neural networks (Computer science)??
9. QUANTUM COMPUTERS
10. Quantum computing
11. QUANTUM INFORMATION
12. QUANTUM PHYSICS
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12944 |
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On Shelf |
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4.
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| 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 |
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On Shelf |
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5.
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| 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 |
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On Shelf |
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6.
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| 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 |
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On Shelf |
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7.
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| 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 |
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On Shelf |
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8.
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| 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 |
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On Shelf |
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9.
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| 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 |
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On Shelf |
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10.
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| 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 |
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On Shelf |
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