A neural-network-based channel-equalization strategy for chaos-based communication systems

This work addresses the channel-distortion problem and proposes a technique for channel equalization in chaos-based communication systems. The proposed equalization is realized by a modified recurrent neural network incorporating a specific training (equalizing) algorithm.