Jove
Visualize
联系我们

相关概念视频

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
106
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

6.1K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
6.1K
Associative Learning01:27

Associative Learning

388
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
388
Reinforcement Schedules01:24

Reinforcement Schedules

148
Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
Once a behavior is learned,...
148
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

8.4K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
8.4K
Difference Equation Solution using z-Transform01:24

Difference Equation Solution using z-Transform

296
The z-transform is a powerful tool for analyzing practical discrete-time systems, often represented by linear difference equations. Solving a higher-order difference equation requires knowledge of the input signal and the initial conditions up to one term less than the order of the equation.
The z-transform facilitates handling delayed signals by shifting the signal in the z-domain, which corresponds to delaying the signal in the time domain, and advancing signals by similarly shifting in the...
296

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Adaptive Learning Control of Uncertain Systems via Weight and Intrinsic Plasticity-Based Neural Networks.

IEEE transactions on neural networks and learning systems·2026
Same author

DPhA-EtOBz-TSC targets cystathionine γ-lyase (CSE) to trigger ferroptosis and inhibit colorectal cancer growth in vitro and in vivo.

European journal of pharmacology·2026
Same author

Prescribed-rate target tracking for time-delayed systems using output measurements.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Inverse Reinforcement Learning for Disturbed Networked Nonlinear Systems With Data Dropouts.

IEEE transactions on neural networks and learning systems·2025
Same author

Distributed FilterNet Reinforcement Learning for Achieving Output Consensus in Heterogeneous Multiplayer Multiagent Systems.

IEEE transactions on neural networks and learning systems·2025
Same author

Dual activation of PPARα/γ by bezafibrate triggers PINK1/Parkin-Mediated mitophagy to enhance lenvatinib sensitivity in hepatocellular carcinoma.

Biochemical pharmacology·2025
Same journal

An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models.

IEEE transactions on cybernetics·2026
Same journal

A Quantum Self-Attention Neural Network Model on Quantum Circuits.

IEEE transactions on cybernetics·2026
Same journal

Semi-Explicit Solution of Some Discrete-Time Higher-Order-Cost Mean-Field-Type Control.

IEEE transactions on cybernetics·2026
Same journal

A Novel One-Step Small Object Detector for Autonomous Aerial Vehicles.

IEEE transactions on cybernetics·2026
Same journal

Online Data-Driven-Based Optimal Output Tracking Control Without Initial Stabilizing Policy.

IEEE transactions on cybernetics·2026
Same journal

Digital Redesign-Based Interval State Estimation for Continuous Systems With Aperiodic Discrete Measurements.

IEEE transactions on cybernetics·2026
查看所有相关文章
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jul 7, 2025

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

5.0K

使用输入输出数据的反向Q学习.

Bosen Lian, Wenqian Xue, Frank L Lewis

    IEEE transactions on cybernetics
    |December 22, 2023
    PubMed
    概括
    此摘要是机器生成的。

    本研究引入了新的反强化学习 (RL) 算法,用于在控制系统中仅使用输入输出数据来学习目标函数. 这些方法通过不要求完整状态信息来推进RL.

    更多相关视频

    An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice
    08:59

    An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice

    Published on: March 3, 2023

    2.1K
    Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
    11:18

    Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

    Published on: June 1, 2015

    10.7K

    相关实验视频

    Last Updated: Jul 7, 2025

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
    08:18

    WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

    Published on: August 15, 2020

    5.0K
    An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice
    08:59

    An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice

    Published on: March 3, 2023

    2.1K
    Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
    11:18

    Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

    Published on: June 1, 2015

    10.7K

    科学领域:

    • 控制系统工程 控制系统工程
    • 机器学习 机器学习
    • 优化优化 优化优化

    背景情况:

    • 传统的反向强化学习 (RL) 方法通常需要从专家演示中获得完整的状态信息和状态反控制.
    • 静态输出-比例-积分-导数 (OPFB) 控制系统由于输入-输出测量有限而存在挑战.

    研究的目的:

    • 开发反向RL算法,用于在静态OPFB控制的线性离散时间系统中学习目标函数.
    • 通过仅使用输入-输出数据来解决现有的反向RL方法的局限性.

    主要方法:

    • 建议使用基于模型的反向RL算法来使用系统动态和OPFB增益来重建输入输出目标函数.
    • 基于状态重建技术开发了一个输出输入的Q函数.
    • 介绍了一种数据驱动的反向Q学习算法,用于从经过证明的输入和输出中学习目标函数,而无需先前的系统知识.

    主要成果:

    • 拟议的算法成功地从输入-输出数据中重建了目标函数和OPFB收益.
    • 数据驱动的算法提供了公正的解决方案,尽管探索噪声.
    • 分析了融合特性和解决方案的非独特性质.

    结论:

    • 开发的反向RL算法有效地学习用于使用有限数据的静态OPFB控制系统的客观函数.
    • 这些方法为控制工程中的反向RL提供了更普遍和实际的方法.
    • 数字模拟证实了拟议技术的有效性.