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Related Concept Videos

False Memories01:18

False Memories

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False memories represent a cognitive distortion in which individuals recall events that did not happen, or remember them in an altered form. This phenomenon highlights the brain's constructive nature in processing and recalling memories, emphasizing that memory is not a perfect representation of past events but rather a dynamic reconstruction influenced by various factors.
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Understanding Deception01:14

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Deception is a pervasive aspect of human communication. Empirical studies have shown that most individuals engage in some form of deceit on a daily basis, with approximately 20% of social exchanges involving deceptive elements. Lying follows a developmental trajectory, peaking during adolescence and declining with age, possibly due to the maturation of cognitive control and social accountability.Cognitive and Social Factors in Deception DetectionDespite its prevalence, accurately detecting...
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    Area of Science:

    • Control Theory
    • Neural Networks
    • Network Security

    Background:

    • Fuzzy memristive neural networks (FMNNs) are crucial for complex computations.
    • Ensuring stability in FMNNs under stochastic disturbances and random deception attacks (RDAs) is a significant challenge.
    • Existing methods for predefined-time stabilization have limitations.

    Purpose of the Study:

    • To introduce and investigate the concept of practically predefined-time stabilization in probability (PPDTSP) for FMNNs.
    • To develop a novel Lyapunov-type criterion for PPDTSP.
    • To design a simplified control scheme for achieving PPDTSP under disturbances and RDAs.

    Main Methods:

    • Introduction of a novel Lyapunov-type criterion for PPDTSP.
    • Development of a simplified, practically predefined-time control scheme.
    • Mathematical analysis and theoretical derivations for stability guarantees.
    • Numerical simulations for validation.

    Main Results:

    • A novel Lyapunov-type criterion for PPDTSP is proposed, which is more general than existing criteria.
    • A simplified control scheme is designed to achieve PPDTSP for FMNNs under stochastic disturbances and RDAs.
    • The proposed method ensures stabilization within a practically predefined time.
    • Special cases of predefined-time stabilization in probability (PDTSP) are derived.

    Conclusions:

    • The proposed PPDTSP concept and criterion effectively address the stabilization of FMNNs under challenging conditions.
    • The developed control scheme provides a practical solution for enhancing the resilience of FMNNs.
    • Numerical simulations confirm the validity and effectiveness of the theoretical findings.