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Related Concept Videos

Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

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In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
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Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
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Output Synchronization via Intermittent Dynamic Event-Triggered Sampled-Data Security Control for Delayed

Zi-Peng Wang, Hong-Yu Chen, Junfei Qiao

    IEEE Transactions on Cybernetics
    |February 16, 2026
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    Summary
    This summary is machine-generated.

    This study introduces a novel intermittent dynamic event-triggered sampled-data (IDETSD) security control for reaction-diffusion neural networks (RDNNs). The method enhances synchronization under deception attacks and network delays.

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    Area of Science:

    • Control Theory
    • Cybersecurity
    • Artificial Intelligence

    Background:

    • Reaction-diffusion neural networks (RDNNs) are crucial in complex system modeling.
    • Ensuring secure control in RDNNs is challenging due to delays and cyberattacks.
    • Existing time-triggered control methods are less effective against sophisticated attacks.

    Purpose of the Study:

    • To develop an intermittent dynamic event-triggered sampled-data (IDETSD) security control for RDNNs.
    • To achieve output synchronization in RDNNs despite delays and random deception attacks.
    • To enhance the resilience of RDNNs against cyber threats.

    Main Methods:

    • Utilizing a dynamic event-triggered (ET) mechanism to mitigate deception attacks.
    • Applying an ET-dependent switched Lyapunov functional (LF) and inequality techniques.
    • Designing the IDETSD controller by solving linear matrix inequalities (LMIs).

    Main Results:

    • Successfully achieved output synchronization for delayed RDNNs under random deception attacks.
    • Demonstrated the effectiveness of the dynamic ET mechanism over traditional time-triggered strategies.
    • Validated the proposed control method through simulation studies.

    Conclusions:

    • The proposed IDETSD security control is effective for RDNNs facing delays and deception attacks.
    • The dynamic ET approach offers superior mitigation of cyberattacks compared to time-triggered methods.
    • The study provides a robust framework for secure and synchronized RDNN control.