Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book explains why complex systems research is important in understanding the structure, function and dynamics of complex natural and social phenomena. It illuminates how complex collective behavior emerges from the parts of a system, due to the interaction between the system and its environment. You will learn the basic concepts and methods of complex system research. It is shown that very different complex phenomena of nature and society can be analyzed and understood by nonlinear dynamics since many systems of very different fields, such as physics, chemistry, biology, economics, psychology and sociology etc. have similar architecture. "Complexity Explained" is not highly technical and mathematical, but teaches and uses the basic mathematical notions of dynamical system theory making the book useful for students of science majors and graduate courses, but it should be readable for a more general audience; actually for those, who ask: What complex systems really are?

Computational Complexity --- Computational complexity. --- Computational complexity --- Complexité de calcul (Informatique) --- EPUB-LIV-FT LIVINGEN SPRINGER-B

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.

Complex analysis --- Mathematical statistics --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- neuronale netwerken --- beeldverwerking --- factoranalyse --- complexe analyse (wiskunde) --- machine learning --- informatica --- KI (kunstmatige intelligentie) --- robots

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Synchronization: From Simple to Complex is devoted to the fundamental phenomenon in physics - synchronization that occurs in coupled non-linear dissipative oscillators. Examples of such systems range from mechanical clocks to population dynamics, from human heart to neural networks. The authors study this phenomenon as applied to oscillations of different nature such as those with periodic, chaotic, noisy and noise-induced nature, reveal the general mechanisms behind synchronization, and bring to light other important effects that accompany synchronization such as phase multistability, dephasing and multimode interaction. The main purpose of this book is to demonstrate that the complexity of synchronous patterns of real oscillating system can be described in the framework of the general approach.

Mathematical physics --- Engineering sciences. Technology --- Computer science --- informatica --- wiskunde --- ingenieurswetenschappen --- fysica