适应性噪音学习差分神经解决方案用于时间依赖的等式受约束的二次优化
IEEE transactions on neural networks and learning systems
|April 30, 2025
概括
本研究介绍了一种适应性噪音学习差异神经解决方案 (ANLDNS) 模型,以解决与噪音相关的复杂优化问题. ANLDNS模型显示了动态系统的强化稳定性和学习能力.
科学领域:
- 计算神经科学是一种神经科学.
- 优化理论 优化理论
- 机器人技术 机器人技术 机器人技术
背景情况:
- 解决依赖时间的等式受约束的二次优化 (TD-ECQO) 问题是具有挑战性的,特别是与现实世界的噪音.
- 现有的方法经常与噪声干扰作斗争,影响准确性和稳定性.
研究的目的:
- 提出一种新的适应性噪音学习差异神经解决方案 (ANLDNS) 模型.
- 为了应对解决TD-ECQO问题和处理噪声的同时挑战.
- 增强基于神经网络的优化系统的强度和学习能力.
主要方法:
- 在差异神经网络中开发一种适应性噪音学习机制.
- 理论分析以证明融合性能和噪音学习能力.
- 通过依赖时间的数值示例和机器人控制应用程序进行验证.
主要成果:
- 在存在噪音的情况下,ANLDNS模型有效地解决了TD-ECQO问题.
- 噪声学习机制通过适应噪声变化来提高模型的稳定性.
- 理论证明证实了该模型的融合和噪音学习能力.
结论:
- 拟议的ANLDNS模型为杂的TD-ECQO问题提供了强大而实用的解决方案.
- 该模型与现有最先进的方法相比,显示出更高的性能.
- 在冗余机器人控制中的应用凸显了其在现实世界的适用性.
相关概念视频
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
25
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
25
Linear time-invariant Systems
177
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...
177
Linear Approximation in Time Domain
53
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
53
Statically Indeterminate Problem Solving
339
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
339
Difference Equation Solution using z-Transform
207
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...
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...
207
Feedback control systems
252
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...
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...
252


