This is an excellent introduction for graduate students and nonspecialists to the field of mathematical and computational neurosciences. The book approaches the subject via pulsed-coupled neural networks, which have at their core the lighthouse and integrate-and-fire models. These allow for highly flexible modeling of realistic synaptic activity, synchronization and spatio-temporal pattern formation. The more advanced pulse-averaged equations are discussed.
Exploring the relationship between Shannon and semantic information, this monograph reveals how both types of information influence cognition. It introduces the concept of information adaptation, where the mind/brain adjusts to environmental information through its quantitative variations and meanings. The authors illustrate their theories mathematically and conceptually, focusing on three cognitive processes: pattern recognition, face learning, and moving object recognition, demonstrating the dynamic interplay between information types in cognitive development.
Implications to Urban Scaling, Smart Cities and Planning
Focusing on urban dynamics, this book presents a unique framework incorporating Synergetics, which examines cooperation and self-organization in cities. It intertwines information theory's semantic and pragmatic elements with optimization principles, while also addressing steady state maintenance and phase transitions to explore qualitative changes in urban structures and behaviors. This interdisciplinary approach provides fresh insights into the complexities of city life and development.
The book offers a comprehensive introduction to synergetics, an expanding field that intersects various scientific disciplines. It features updated discussions on key topics like self-organization in extended media and Benard instability, as well as an economic model illustrating transitions from full employment to underemployment using nonequilibrium phase transitions. Additionally, it includes a new section on discrete maps, which are essential for exploring chaotic motion and related phenomena. The third edition reflects significant recent developments and aims to enhance readability.
Instability Hierarchies of Self-Organizing Systems and Devices
The book explores the concept of self-organization across various disciplines, illustrating how systems in nature and technology develop structures and functions independently. It addresses the commonality of instabilities in both biological processes, like cell differentiation and evolution, and engineered devices, such as electronic oscillators. By examining the interplay between natural self-organization and man-made systems, the text highlights the fluid boundary between them, making it relevant for a diverse audience in science and engineering.
A Macroscopic Approach to Complex Systems
Cognitive science serves as a central theme, bridging disciplines such as mathematics, physics, and psychology through the concept of information. This edition introduces three new chapters that explore the interplay between Shannon information and semantic information, emphasizing how meaning influences cognitive processes. Additionally, it covers the emerging fields of quantum information and quantum computation, highlighting the essential connection between abstract information concepts and their physical realizations.
A Synergetic Approach to Brain Activity, Behavior and Cognition
The book emphasizes the necessity of interdisciplinary collaboration in brain research, integrating insights from biology, medicine, physics, and more. It targets graduate students, professors, and scientists, offering a blend of mathematical, verbal, and pictorial representations to convey essential concepts, making it accessible to a wider audience. The author acknowledges the contributions of former students and colleagues, highlighting the importance of diverse perspectives in advancing understanding of the brain's complex systems.
Introduction to Experiments and Theory
This second edition of the textbook incorporates significant advancements in molecular physics, particularly focusing on single-molecule spectroscopy and the rapidly evolving field of molecular electronics, including electroluminescence and organic light-emitting diodes. The content has been expanded and corrected from the first edition, and new exercises are provided to enhance student understanding, with complete solutions available online. Aimed at students of physics and related fields, it assumes prior knowledge of atomic and quantum physics.
The book presents a comprehensive modeling framework for psychotherapy, integrating recent research findings. It emphasizes the importance of the therapist-client alliance and explores how therapeutic interventions are influenced by both deterministic and stochastic forces. Utilizing a Fokker-Planck approach alongside complexity theory's structural-mathematical framework, the authors provide a nuanced understanding of the dynamics at play in effective therapy.
This book explores the innovative concept of the synergetic computer, presenting it as a significant alternative to traditional neural networks. It highlights advantages such as the elimination of ghost states and the explicit determination of synaptic strengths, which enhance learning and classification processes. The second edition introduces new sections on transformation properties and stereopsis, while also addressing the application of pulse-coupled neural nets in pattern recognition. It serves as a valuable resource for scientists, engineers, and graduate students in informatics and psychology.