Dynamical neural networks proved to be an important tool to solve some practical engineering problems in the areas such as optimization, image and signal processing, control systems, associative memories, and pattern recognition. When employing neural networks to solve practical engineering problems, it is crucial to be able to completely characterize the dynamical properties of neural networks. There are many various classes of neural network models that can be described in the form of nonlinear systems. Therefore, neural networks may exhibit extremely different complex dynamical behaviors depending on the model and network parameters. Hence, the analysis of nonlinear dynamics of neural networks still possesses new challenges to researchers. We invite authors to submit original research and review articles focusing on the analysis of nonlinear dynamics of neural networks. Potential topics include, but are not limited to:

• Analysis and modeling of biological neural networks
• Mathematical and computational analysis
• Convergence and stability analysis
• Cognitive neurodynamics and complex systems
• Attractors and associative memories
• Fuzzy neural networks
• Learning systems
• Spiking neurons
• Multiscale analysis

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/aaa/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable: