Anti-Periodic Synchronization of Clifford-Valued Neutral-Type Recurrent Neural Networks With <italic>D</italic> Operator

Abstract

In this paper, a class of Clifford-valued neutral-type recurrent neural networks with $D$ operator is explored. By using non-decomposition method and the Banach fixed point theorem, we obtain several sufficient conditions for the existence of anti-periodic solutions for Clifford-valued neutral-type recurrent neural networks with $D$ operator. By using the proof by contradiction and inequality techniques, we obtain the global exponential synchronization of anti-periodic solutions for Clifford-valued neutral-type recurrent neural networks with $D$ operator. Finally, we give one example to illustrate the feasibility and effectiveness of main results.

Keywords

• Clifford algebra
• recurrent neural networks
• synchronization
• anti-periodic solutions
• D operator%22%2C%22default_operator%22%3A%22AND%22%7D%7D%7D"> <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">D</italic> operator