| [1] |
Chaos and Complexity |
| [2] |
The Chaos Revolution |
| [3] |
Complex Dynamical Systems |
| [4] |
Dynamics of Hyperspace |
| [5] |
The Dynamics of Synchronization and Phase Regulation |
| [6] |
The Genesis of Complexity |
| [7] |
The Geometry of the Soul |
| [8] |
Landscape Dynamics, Complex Dynamics, and Agent Based Models |
| [9] |
Sacred Mathematics and the Chaos Revolution |
| [10] |
Social Synergy Models |
| [11] |
A Stairway to Chaos |
| [12] |
Dynamical Systems: A Visual Introduction |
| [13] |
Adaptive Cognitive Systems |
| [14] |
Self Organization and Chaos in Collective Phenomena |
| [15] |
Large-scale agent-based models |
| [16] |
Dynamics of massive multiagent economies |
| [17] |
NetLogo User's Guide |
| [18] |
NetLogo 2.1.0 User Manual |
| [19] |
Complexity / Art and Complex Systems |
| [20] |
Evolutionary Systems and Semantics of Information |
| [21] |
n-Dimensional Visualization |
| [22] |
Aspects on Data Analysis and Visualization for Complex Dynamical Systems |
| [23] |
Visualizing Complexity in Networks |
| [24] |
Complexity and Robustness |
| [25] |
Computational Complexity |
| [26] |
The Computational Complexity Column |
| [27] |
Lecture Notes on Computational Complexity |
| [28] |
Interdisciplinary application of nonlinear time series methods |
| [29] |
Numerical Mathematics |
| [30] |
A proposed name for aperiodic brain activity: stochastic chaos |
| [31] |
Complexity in Biological Signaling Systems |
| [32] |
Measurements of brain activity complexity for varying mental loads |
| [33] |
Modelling of cognitive complexity with Petri nets |
| [34] |
Structural, Functional and
Dynamic Modules. Department of Biophysics |
| [35] |
Consciousness: Scientific Challenge of the 21st Century |
| [36] |
Consciousness and Complexity |
| [37] |
Journal of Accelerated Learning and Teaching |
| [38] |
The Structure of Intelligence: A New Mathematical Model of Mind |
| [39] |
Complexity - Dependent Synchronization of Brain Subsystems During Memorization |
| [40] |
Ultimate Computing: Biomolecular Consciousness and NanoTechnology |
| [41] |
Basic Concepts in Nonlinear Dynamics and Chaos |
| [42] |
Catastrophe Theory |
| [43] |
Simple Connectivity and Linear Chaos |
| [44] |
Deterministic Nonperiodic Flow. |
| [45] |
Bifurcation structure of the generalized Henon map |
| [46] |
What kinds of dynamics are there? Lie pseudogroups, dynamical systems, and geometric integration |
| [47] |
Overview of complexity and decidability results for three classes of elementary nonlinear systems |
| [48] |
Estimating generating partitions of chaotic systems by unstable periodic orbits |
| [49] |
Interactive Visualization of Quaternion Julia Sets |
| [50] |
Designing agent-based market models |
| [51] |
Toward Agent-Based Models for Investment |
| [52] |
The Building Blocks of Complexity: a unified criterion and selected applications in economics and finance |
| [53] |
Complexity and the Economy |
| [54] |
Multifractal Analysis and Local Hoelder Exponents Approach to Detecting Stock Markets Crashes |
| [55] |
Economics: the next physical science? |
| [56] |
Advanced Modeling, Visualization, and Data Mining Techniques for a New Risk Landscpape |
| [57] |
A Multifractal Model of Asset Returns |
| [58] |
Ten years of genetic fuzzy systems: current framework and new trends |
| [59] |
Adaptive Resonance Theory (ART): An Introduction |
| [60] |
Adaptive Resonance Theory |
| [61] |
Adaptive Resonance Theory |
| [62] |
Artificial Neural Networks Technology |
| [63] |
Computational Learning Theory: Lecture Notes for CS 582. Department of Computer Science
Washington University |
| [64] |
Computational Learning Theory for Artificial Neural Networks. |
| [65] |
Functional Learning with Wavelets |
| [66] |
Genetic Algorithm Dynamics on a Rugged Landscape |
| [67] |
Hybrid Soft Computing Systems: Where Are We Going? |
| [68] |
An Introduction to Neural Nets |
| [69] |
An Introduction to Kernal-Based Learning Algorithms |
| [70] |
Neuro–Fuzzy Rule Generation: Survey in Soft Computing Framework |
| [71] |
Progress in Supervised Neural Networks |
| [72] |
A Tutorial on Support Vector Machines. |
| [73] |
Algebraic Topology |
| [74] |
Natural Operations in Differential Geometry |
| [75] |
Information Theory, Inference, and Learning Algorithms |
| [76] |
Machine Learning, Neural and Statistical Classification |
| [77] |
Neural Network Toolbox For Use with MATLAB |
| [78] |
Calculus Volume II: Mlulti-Variable Calculus and Linear Algebra, with Applications to Differential Equations and Probability |
| [79] |
Ordinary differential equations and Dynamical Systems |
| [80] |
Complexity and synchronization of the World trade Web |
| [81] |
Statistical Mechanics of Networks |
| [82] |
Dynamics of Social Networks |
| [83] |
Emergence of a Small World from Local Interactions: Modeling Acquaintance Networks |
| [84] |
Some Streams of Systemic Thought |
| [85] |
Synchronization in Complex Dynamical Networks and Its Applications |
| [86] |
One Hundred Years of Quantutm Physics |
| [87] |
Classical Chaos and its Quantum Manifestations |
| [88] |
A Short Histtory of the Missing Mass and Dark Energy Paradigms |
| [89] |
Hilbert's First Note on the Foundation of Physics |
| [90] |
Early History of Gauge Theories and Kaluza-Klein: Theories, with a Glance at Recent Developments |
| [91] |
Why Magnetized Target Fusion Offers A Low-Cost Development Path for Fusion Energy |
| [92] |
Notes on Hilbert Space. Department of Physics |
| [93] |
A Historical Perspective on the Topology and Physics of Hyperspace |
| [94] |
Progress in Post-Quantum Theory |
| [95] |
What Is The Universe Made Of? |
| [96] |
Zero Point Energy |
| [97] |
Artificial Neural Net Attractors |
| [98] |
Routes to Chaos in Neural Networks with Random Weights |
| [99] |
Elementary Chaotic Flow |
| [100] |
Simplest Dissipative Chaotic Flow |
| [101] |
Complex systems under stochastic dynamics |
| [102] |
Statistical mechanics of complex networks |
| [103] |
Stochastic Calculus Notes |
| [104] |
Phase-Space Transport of Stochastic Chaos in Population Dynamics of Virus Spread |
| [105] |
An Introduction To Stochastic Differential Equations |
| [106] |
The stable manifold theorem for non-linear stochastic systems with memory |
[107] |
From Chaos to Cryptography |
| [108] |
Chaos, Complexity, and Accident |
| [109] |
Scale Analysis by the Continuous Wavelet Transform |
| [110] |
Defining Complexity |
| [111] |
An Introduction to Wavelets |
| [112] |
Nonlinear Science 2001/2002 Catalogue |