Neural networks : the official journal of the International Neural Network Society
Feb 10, 2025
For unknown nonlinear systems with state constraints, it is difficult to achieve the safe optimal control by using Q-learning methods based on traditional quadratic utility functions. To solve this problem, this article proposes an accelerated safe Q...
Neural networks : the official journal of the International Neural Network Society
Feb 1, 2025
Artificial neural networks are receiving increasing attention from researchers. However, with the advent of big data era, artificial neural networks are limited by the Von Neumann architecture, making it difficult to make new breakthroughs in hardwar...
Conjugate Gradient (CG) methods are widely used for solving large-scale nonlinear systems of equations arising in various real-life applications due to their efficiency in employing vector operations. However, the global convergence analysis of CG me...
Brain tumours are one of the most deadly and noticeable types of cancer, affecting both children and adults. One of the major drawbacks in brain tumour identification is the late diagnosis and high cost of brain tumour-detecting devices. Most existin...
Neural networks : the official journal of the International Neural Network Society
Jan 17, 2025
In this work, we present the novel mathematical framework of latent dynamics models (LDMs) for reduced order modeling of parameterized nonlinear time-dependent PDEs. Our framework casts this latter task as a nonlinear dimensionality reduction problem...
Neural networks : the official journal of the International Neural Network Society
Jan 16, 2025
The Physics-informed Neural Network (PINN) has been a popular method for solving partial differential equations (PDEs) due to its flexibility. However, PINN still faces challenges in characterizing spatio-temporal correlations when solving parametric...
Neural networks : the official journal of the International Neural Network Society
Jan 13, 2025
This paper discusses the nuanced domain of nonlinear feature selection in heterogeneous systems. To address this challenge, we present a sparsity-driven methodology, namely nonlinear feature selection for support vector quantile regression (NFS-SVQR)...
Neural networks : the official journal of the International Neural Network Society
Jan 6, 2025
Nonsmooth nonconvex optimization problems are pivotal in engineering practice due to the inherent nonsmooth and nonconvex characteristics of many real-world complex systems and models. The nonsmoothness and nonconvexity of the objective and constrain...
By gaining insights into how brain activity is encoded and decoded, we enhance our understanding of brain function. This study introduces a method for classifying EEG signals related to visual objects, employing a combination of an LSTM network and n...
Neural networks : the official journal of the International Neural Network Society
Dec 31, 2024
Reservoir computing, using nonlinear dynamical systems, offers a cost-effective alternative to neural networks for complex tasks involving processing of sequential data, time series modeling, and system identification. Echo state networks (ESNs), a t...
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