Dynamic ANNs have the ability to track time variation in the samples applied. These are relevant for time series modeling, speech processing and all such phenomena where there are marked time dependences. ANNs with memory or delay elements in the input, output or hidden sections demonstrate dynamic behavior. Further, Recurrent Neural networks are known to posses such ability. This lecture focuses on the different aspects of dynamic ANNs.
