Autors: Stamov, T. G.
Title: Discrete Bidirectional Associative Memory Neural Networks of the Cohen–Grossberg Type for Engineering Design Symmetry Related Problems: Practical Stability of Sets Analysis
Keywords: BAM neural networks; Cohen–Grossberg types; engineering desi

Abstract: In recent years, artificial intelligence techniques have become fundamental parts of various engineering research activities and practical realizations. The advantages of the neural networks, as one of the main artificial intelligence methods, make them very appropriate for different engineering design problems. However, the qualitative properties of the neural networks’ states are extremely important for their design and practical performance. In addition, the variety of neural network models requires the formulation of appropriate qualitative criteria. This paper studies a class of discrete Bidirectional Associative Memory (BAM) neural networks of the Cohen–Grossberg type that can be applied in engineering design. Due to the nature of the proposed models, they are very suitable for symmetry-related problems. The notion of the practical stability of the states with respect to sets is introduced. The practical stability analysis is conducted by the method of the Lyapunov functions. Ex

References

    Issue

    Symmetry, vol. 14, issue 2, 2022, Switzerland, Basel, MDPI

    Цитирания (Citation/s):
    1. Lipschitz stability analysis of fractional-order impulsive delayed reaction-diffusion neural network models - 2022 - в издания, индексирани в Scopus или Web of Science
    2. Extended Stability and Control Strategies for Impulsive and Fractional Neural Networks: A Review of the Recent Results - 2023 - в издания, индексирани в Scopus или Web of Science
    3. Lyapunov approach to manifolds stability for impulsive Cohen–Grossberg-type conformable neural network models - 2023 - в издания, индексирани в Scopus или Web of Science
    4. Impulsive Controllers Design for the Practical Stability Analysis of Gene Regulatory Networks with Distributed Delays - 2023 - в издания, индексирани в Scopus или Web of Science
    5. Generic Model of Max Heteroassociative Memory Robust to Acquisition Noise - 2023 - в издания, индексирани в Scopus или Web of Science
    6. Lipschitz Quasistability of Impulsive Cohen–Grossberg Neural Network Models with Delays and Reaction-Diffusion Terms - 2023 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus и Web of Science