Jove
Visualize
联系我们
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

相关概念视频

Pole and System Stability01:24

Pole and System Stability

298
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
298
Control System Problem01:21

Control System Problem

118
In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...
118
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

398
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....
398
Stability of Equilibrium Configuration: Problem Solving01:13

Stability of Equilibrium Configuration: Problem Solving

606
The stability of equilibrium configurations is an important concept in physics, engineering, and other related fields. In simple terms, it refers to the tendency of an object or system to return to its equilibrium position after being disturbed. The stability of an equilibrium configuration can be analyzed by considering the potential energy function of the system and examining its behavior near the equilibrium point.
Problem-solving in the context of the stability of equilibrium configuration...
606
Root Loci for Positive-Feedback Systems01:23

Root Loci for Positive-Feedback Systems

122
The Hartley oscillator is a positive feedback system that sustains oscillations by feeding the output back to the input in phase, thereby reinforcing the signal. Positive feedback systems can be viewed as negative feedback systems with inverted feedback signals. In these systems, the root locus encompasses all points on the s-plane where the angle of the system transfer function equals 360 degrees.
The construction rules for the root locus in positive feedback systems are similar to those in...
122
Stability of Equilibrium Configuration01:23

Stability of Equilibrium Configuration

448
Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
A stable equilibrium occurs when a system tends to return to its original position when given a small displacement, and the potential energy is at its minimum. An example of a stable equilibrium is when a cantilever beam is fixed at one end and a weight is attached to the other end. If the weight...
448

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

Attractor-Based Models for Sequences and Pattern Generation in Neural Circuits.

Neural computation·2026
Same author

Topological analysis of neuronal assemblies reveals low-rank structure modulated by cholinergic activity.

bioRxiv : the preprint server for biology·2025
Same author

Central Adiposity and Visceral Fat in Long-Term Survivors of Acute Lymphoblastic Leukemia in Childhood and Adolescence: Exploration of an Underappreciated Risk.

Pediatric blood & cancer·2025
Same author

Diet quality in relation to serum perfluoroalkyl substance concentrations in Canadian preadolescents.

Environmental research·2025
Same author

Topological Neuroscience: Linking Circuits to Function.

Annual review of neuroscience·2025
Same author

AAHPM Assessment Workgroup: Hospice and Palliative Medicine Fellowship Assessment Needs and Directions.

Journal of pain and symptom management·2024
Same journal

Geometry of the space of phylogenetic trees with non-identical leaves.

Advances in applied mathematics·2026
Same journal

Enumeration of coalescent histories for caterpillar species trees and <i>p</i>-pseudocaterpillar gene trees.

Advances in applied mathematics·2021
Same journal

Horizontal visibility graph of a random restricted growth sequence.

Advances in applied mathematics·2021
Same journal

Roadblocked monotonic paths and the enumeration of coalescent histories for non-matching caterpillar gene trees and species trees.

Advances in applied mathematics·2020
Same journal

ENUMERATION OF LONELY PAIRS OF GENE TREES AND SPECIES TREES BY MEANS OF ANTIPODAL CHERRIES.

Advances in applied mathematics·2019
Same journal

RECOVERING A TREE FROM THE LENGTHS OF SUBTREES SPANNED BY A RANDOMLY CHOSEN SEQUENCE OF LEAVES.

Advances in applied mathematics·2018
查看所有相关文章

相关实验视频

Updated: Jul 5, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.2K

结合的值线性网络的稳定固定点.

Carina Curto, Jesse Geneson, Katherine Morrison

    Advances in applied mathematics
    |January 22, 2024
    PubMed
    概括
    此摘要是机器生成的。

    组合值线性网络 (CTLNs) 的动态是由图表所支配的. 这项研究证明,CTLN图形中的无目标小组是唯一稳定的固定点,增强了关联记忆模型.

    关键词:
    15 15 15 15 15 的时间.34 34 34 34 34 34 34 34 34 34 34 34 34 34 这是一个很大的问题.92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 when when when when when when when when when when when when when when when when when when when when科拉茨 - 维兰特公式吸引子神经网络是一种神经网络.这些小组,小组,小组,小组,小组.稳定的固定点是稳定的固定点.值线性网络是一个线性网络.

    更多相关视频

    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
    07:34

    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

    Published on: March 25, 2014

    9.9K
    Generating Strictly Controlled Stimuli for Figure Recognition Experiments
    05:39

    Generating Strictly Controlled Stimuli for Figure Recognition Experiments

    Published on: March 18, 2019

    5.2K

    相关实验视频

    Last Updated: Jul 5, 2025

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
    10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.2K
    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
    07:34

    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

    Published on: March 25, 2014

    9.9K
    Generating Strictly Controlled Stimuli for Figure Recognition Experiments
    05:39

    Generating Strictly Controlled Stimuli for Figure Recognition Experiments

    Published on: March 18, 2019

    5.2K

    科学领域:

    • 计算神经科学是一种计算神经科学.
    • 图形理论是指图形的理论.
    • 机器学习是机器学习.

    背景情况:

    • 经常性神经网络,包括组合值线性网络 (CTLNs),被用作关联记忆和模式完成的模型.
    • 这些网络中的稳定固定点代表存储的记忆模式.
    • 之前的研究已经确定了CTLN图中的无目标小组与稳定的固定点之间的对应,推测这些是唯一可能的稳定的固定点.

    研究的目的:

    • 以数学证明无目标小组是组合值线性网络中唯一稳定的固定点的猜测.
    • 探索这种猜想的条件和局限性.
    • 在CTLN中设置稳定的固定点数的限制.

    主要方法:

    • 对于特定的网络和图形属性 (例如,强大的抑制,小的图形大小) 的假设的数学证明.
    • 分析图形结构 (散点和近点图形),以证明没有稳定的固定点.
    • 应用极端组合学来推导稳定的固定点数量的边界.

    主要成果:

    • 无目标小组与唯一稳定的固定点相对应的猜测已被证实在CTLN的几个特殊情况下.
    • 提供了证据表明,稀疏的图形和几乎是集群的图形不支持稳定的固定点.
    • 稳定的固定点数的上限是通过极端组合学的结果来得出的.

    结论:

    • 该研究证实了对特定CTLN配置的猜测,巩固了图形结构和网络动态之间的联系.
    • 这些发现有助于更深入地了解关联记忆模型和神经网络中的模式完成.
    • 衍生出来的边界为CTLN作为内存系统的容量和复杂性提供了见解.