edited by Kyandoghere Kyamakya (University of Klagenfurt, Austria), Abdelhamid Bouchachia (University of Klagenfurt, Austria), & Jean C Chedjou (University of Klagenfurt, Austria)

Over the past years, the appropriateness of Computational Intelligence (CI) techniques in modeling and optimization tasks pertaining to complex nonlinear dynamic systems has become indubitable, as attested by a large number of studies reporting on the successful application of CI models in nonlinear science (for example, adaptive control, signal processing, medical diagnostic, pattern formation, living systems, etc.).

This volume summarizes the state-of-the-art of CI in the context of nonlinear dynamic systems and synchronization. Aiming at fostering new breakthroughs, the chapters in the book focus on theoretical, experimental and computational aspects of recent advances in nonlinear science intertwined with computational intelligence techniques. In addition, all the chapters have a tutorial-oriented structure.

• Computational Intelligence:
  • Adaptive Computational Intelligence for Dynamical Systems (A Bouchachia)
  • Mealy Finite State Machines: A Quantum Inspired Evolutionary Approach (N Nedjah et al.)
  • Parallel Implementations for Computing the False Nearest Neighbors Method (I M Carrión et al.)
• Pattern Recognition and Nonlinear Systems Techniques:
  • Modeling Gene Expression Dynamics by Kernel Auto-Regressive Models for Time-Course Microarray Data (S Young)
  • Investigating the Usability of SIFT Features in Biometrics (D R Kisku et al.)
  • Super Resolution Challenges and Rewards (A A Hefnawy)
• Application of CI in Nonlinear Dynamic Systems:
  • Financial Markets Analysis: Can Nonlinear Science Contribute? (A T Vouldis)
  • Nonlinear Structural Dynamics and Seismic Control Synchronization (S Radeva)
  • Clustering in VANETs (S Momeni & M Fathy)