Neural networks have been successfully employed in various areas such as pattern recognition, associative memory, and combinatorial optimization. While an artificial neural network has been known insofar for its transient processing behavior, its circuit design has never been disentangled from destabilizing factors such as delays and impulses. In hardware implementation, time delays occur due to finite switching speed of the amplifiers and communication time. Time delays will affect the stability of designed neural networks and may lead to some complex dynamic behaviors such as periodic oscillation, bifurcation, or chaos. Impulses can make unstable systems stable so they have been widely used in many fields such as physics, chemistry, biology, population dynamics, and industrial robotics. The abrupt changes in the voltages produced by faulty circuit elements are exemplary of impulse phenomena that can affect the transient behavior of the network.

We invite investigators to contribute original research articles as well as review articles that will stimulate the continuing efforts to understand the dynamic activity patterns in neural networks. Potential topics include, but not limited to:

• Hopfield neural networks
• Cellular neural networks
• Bidirectional associative memory neural networks
• Lotka-Volterra neural networks
• Neural networks with delays
• Impulsive neural networks
• Stability
• Periodicity
• Almost periodicity
• Control
• Stabilization

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/jam/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: