一个以多项式为基础的等级依赖的相互凸矩阵不等式及其应用于延迟神经网络的稳定性分析
IEEE transactions on cybernetics
|February 28, 2024
概括
本研究引入了使用基于多项式的互矩阵不等式 (RCMI) 的时间变化延迟神经网络 (DNN) 的新稳定性标准. 新方法为分析DNN稳定性提供了不那么保守的结果.
科学领域:
- 控制理论 控制理论
- 人工智能的人工智能
- 计算神经科学是一种神经科学.
背景情况:
- 延迟神经网络 (DNN) 在建模复杂系统中至关重要.
- 对于时间变化的DNN,现有的稳定性标准可能过于保守.
- 减少保守主义是准确分析和控制设计的关键.
研究的目的:
- 为变化时间的DNN开发改进和不那么保守的稳定性标准.
- 引入一种基于多项式的相对凸矩阵不等式 (RCMI).
- 加强动态神经网络模型中的稳定性分析.
主要方法:
- 提出了一种基于多项式的相对凸矩阵不等式 (RCMI) 的新型度依赖多项式.
- RCMI允许随时变化的延迟中任意度的多项式,减少保守主义.
- 提出了一个改进的定理,用于管理与高度项相关的计算复杂性.
主要成果:
- 与现有方法相比,拟议的RCMI产生了不那么保守的稳定性标准.
- 这种方法有效地减少了对时间变化的DNN分析的保守主义.
- 通过两个说明性例子证明了它的有效性.
结论:
- 开发的稳定性标准为时间变化的DNN提供了更轻松,更准确的分析.
- 基于多项式的RCMI和改进的定理有助于减少保守主义和可管理的计算.
- 这项工作推进了复杂的延迟神经网络系统的稳定性分析.
更多相关视频
11:18Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
10.3K
06:44Quantitative Analysis of Mitochondria-Associated Endoplasmic Reticulum Membrane (MAM) Stabilization in a Neural Model of Alzheimer's Disease (AD)
Published on: January 10, 2025
476
相关概念视频
Multimachine Stability
153
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
153
Pole and System Stability
295
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...
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...
295
Linear Approximation in Frequency Domain
89
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
89
BIBO stability of continuous and discrete -time systems
395
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....
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....
395
Routh-Hurwitz Criterion II
246
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
246
Linear time-invariant Systems
258
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
258
