AIMC Journal:
IEEE transactions on neural networks and learning systems
Showing 301 to 310 of 780 articles
Online Optimal Adaptive Control of Partially Uncertain Nonlinear Discrete-Time Systems Using Multilayer Neural Networks.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
This article intends to address an online optimal adaptive regulation of nonlinear discrete-time systems in affine form and with partially uncertain dynamics using a multilayer neural network (MNN). The actor-critic framework estimates both the optim...
Probabilistic, Recurrent, Fuzzy Neural Network for Processing Noisy Time-Series Data.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
The rapidly increasing volumes of data and the need for big data analytics have emphasized the need for algorithms that can accommodate incomplete or noisy data. The concept of recurrency is an important aspect of signal processing, providing greater...
Item Relationship Graph Neural Networks for E-Commerce.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
In a modern e-commerce recommender system, it is important to understand the relationships among products. Recognizing product relationships-such as complements or substitutes-accurately is an essential task for generating better recommendation resul...
Joint Label Inference and Discriminant Embedding.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
Graph-based learning in semisupervised models provides an effective tool for modeling big data sets in high-dimensional spaces. It has been useful for propagating a small set of initial labels to a large set of unlabeled data. Thus, it meets the requ...
A Gradient-Guided Evolutionary Approach to Training Deep Neural Networks.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
It has been widely recognized that the efficient training of neural networks (NNs) is crucial to classification performance. While a series of gradient-based approaches have been extensively developed, they are criticized for the ease of trapping int...
Input-to-State Representation in Linear Reservoirs Dynamics.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
Reservoir computing is a popular approach to design recurrent neural networks, due to its training simplicity and approximation performance. The recurrent part of these networks is not trained (e.g., via gradient descent), making them appealing for a...
Neural Networks Enhanced Optimal Admittance Control of Robot-Environment Interaction Using Reinforcement Learning.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
In this paper, an adaptive admittance control scheme is developed for robots to interact with time-varying environments. Admittance control is adopted to achieve a compliant physical robot-environment interaction, and the uncertain environment with t...
Evolutionary Shallowing Deep Neural Networks at Block Levels.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
Neural networks have been demonstrated to be trainable even with hundreds of layers, which exhibit remarkable improvement on expressive power and provide significant performance gains in a variety of tasks. However, the prohibitive computational cost...
Multistability and Stabilization of Fractional-Order Competitive Neural Networks With Unbounded Time-Varying Delays.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
This article investigates the multistability and stabilization of fractional-order competitive neural networks (FOCNNs) with unbounded time-varying delays. By utilizing the monotone operator, several sufficient conditions of the coexistence of equili...
Pinning Impulsive Synchronization of Stochastic Delayed Neural Networks via Uniformly Stable Function.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
This article investigates the synchronization of stochastic delayed neural networks under pinning impulsive control, where a small fraction of nodes are selected as the pinned nodes at each impulsive moment. By proposing a uniformly stable function a...
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