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相关概念视频

Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

267
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.
In the...
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Basic Continuous Time Signals01:22

Basic Continuous Time Signals

216
Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...
216
Feedback control systems01:26

Feedback control systems

319
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
319
Classification of Systems-II01:31

Classification of Systems-II

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Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
150
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

406
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
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Control Systems01:10

Control Systems

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Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
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相关实验视频

Updated: Jul 12, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
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基于和功能的连续控制,对竞争神经网络的固定时间同步进行固定时间同步.

Caicai Zheng1, Cheng Hu2, Juan Yu2

  • 1College of Mathematics and System Science, Xinjiang University, Urumqi, 830017, China.

Neural networks : the official journal of the International Neural Network Society
|October 19, 2023
PubMed
概括

本研究介绍了竞争性人工神经网络 (ANN) 中固定时间 (FXT) 同步的连续控制策略,通过整合短期和长期记忆模型来简化分析. 新方法避免了聊天,并提高了同步性能.

关键词:
有竞争力的神经网络.连续控制的连续控制.FXT同步的同步方式固定时间 (FXT) 稳定性和功能的功能

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科学领域:

  • 人工智能的人工智能
  • 计算神经科学是一种神经科学.
  • 控制理论 控制理论

背景情况:

  • 通过不连续控制和对短期记忆 (STM) 和长期记忆 (LTM) 的单独分析,研究了竞争性人工神经网络 (ANN) 的固定时间 (FXT) 同步.
  • 传统方法存在复杂的衍生,严格的同步条件,以及由于 signum 函数的喋喋不休而导致的性能降低.

研究的目的:

  • 为了应对竞争性ANN在FXT同步中的复杂性和性能降低的挑战.
  • 开发新的连续控制方案,以实现FXT同步,提高效率和稳定性.
  • 通过将STM和LTM模型集成到一个统一的系统中来减少理论复杂性.

主要方法:

  • 通过压缩竞争ANN的STM和LTM模型来建立一个高维系统模型.
  • 开发了一个具有切换差异条件的固定时间稳定定理,提供高精度的收时间估计.
  • 连续纯功率法控制方案是使用和函数设计的,取代了传统的 signum 函数.

主要成果:

  • 拟议的方法通过统一STM和LTM模型来简化理论分析.
  • 基于和函数的连续控制方案有效实现FXT同步,避免聊天.
  • 同步标准通过数值示例来导出和验证,证明其适用于图像加密.

结论:

  • 该研究提出了一种更有效,更不复杂的方法,用于在竞争性ANN中实现固定时间同步.
  • 与现有方法相比,开发的连续控制策略提供了更好的性能和稳定性.
  • 这些发现在安全图像加密等领域有潜在的应用.