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相关概念视频

State Space Representation01:27

State Space Representation

166
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
166
Mason's Rule01:20

Mason's Rule

267
Mason's rule is a powerful tool in control systems and signal processing. It simplifies the calculation of transfer functions from signal-flow graphs. This method leverages various elements, including loop gains, forward-path gains, and non-touching loops, to determine the transfer function efficiently.
Loop gain is determined by identifying and tracing a path from a node back to itself. This involves computing the product of branch gains along the loop. Each loop's gain is crucial for...
267
Cascaded Op Amps01:16

Cascaded Op Amps

594
Operational amplifiers (op-amps) are versatile electronic components that can be interconnected in a cascade - one after another in a linear sequence. This cascading is possible due to their infinite input resistance and zero output resistance, allowing them to maintain their input-output relationships even when connected in series.
In a cascaded system, each op-amp is referred to as a stage. The output of one stage drives the input of the subsequent stage. As the input signal passes through...
594

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相关实验视频

Updated: Jun 9, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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基于token-bucket-protocol的复杂网络的递归远程状态估计在放大和转发中继下.

Tong-Jian Liu, Zidong Wang, Yang Liu

    IEEE transactions on neural networks and learning systems
    |October 25, 2024
    PubMed
    概括

    本研究引入了一种新的递归估计器,用于使用令牌桶协议 (TBP) 和放大和转发 (AF) 继电器的非线性复杂网络. 这项研究量化了TBP.

    科学领域:

    • 控制系统工程 控制系统工程
    • 网络化系统 网络化系统
    • 信号处理 信号处理

    背景情况:

    • 网络状态估计对于复杂系统至关重要.
    • 现有的方法往往忽略了数据传输的限制.
    • 代币桶协议 (TBP) 在信号传输中引入了随机性.

    研究的目的:

    • 在TBP和AF中继下开发非线性复杂网络的递归远程估计算法.
    • 分析TBP对网络状态估计性能的影响.
    • 为了最大限度地减少估计错误的协差.

    主要方法:

    • 设计了一个扩展的基于卡尔曼波器的递归估计器.
    • 里卡蒂式差异方程被解决到有限的误差共变量.
    • 估计器增益被优化,以最大限度地减少误差.
    • 使用了代币消费和道系数的随机建模.

    主要成果:

    • 对于受TBP限制的系统,提出了一种新的递归估计器.
    • 预测/估计误差共变率的上限得到了推导.
    • 量化了TBP对估计性能的影响.
    • 数字模拟验证了估计器的有效性.

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    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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    结论:

    • 拟议的估计器有效地处理具有TBP和AF继电器的非线性复杂网络.
    • TBP显著影响了网络状态估计性能.
    • 开发的方法提供了一个强大的方法,在通信限制下进行远程估计.