Published January 1, 2019 | Version v1
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Mittag-Leffler stability analysis of fractional discrete-time neural networks via fixed point technique

  • 1. Neijiang Normal Univ, Coll Math & Informat Sci, Data Recovery Key Lab Sichuan Prov, Neijiang 641100, Peoples R China
  • 2. Prince Sultan Univ, Dept Math & Gen Sci, POB 66833, Riyadh 11586, Saudi Arabia
  • 3. Nanjing Univ Finance & Econ, Coll Informat Engn, Nanjing 210023, Jiangsu, Peoples R China
  • 4. Neijiang Normal Univ, Coll Math & Informat Sci, Numer Simulat Key Lab Sichuan Prov, Neijiang 641110, Peoples R China

Description

A class of semilinear fractional difference equations is introduced in this paper. The fixed point theorem is adopted to find stability conditions for fractional difference equations. The complete solution space is constructed and the contraction mapping is established by use of new equivalent sum equations in form of a discrete Mittag-Leffler function of two parameters. As one of the application, finite-time stability is discussed and compared. Attractivity of fractional difference equations is proved, and Mittag-Leffler stability conditions are provided. Finally, the stability results are applied to fractional discrete-time neural networks with and without delay, which show the fixed point technique's efficiency and convenience.

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