Security at the physical layer (PHY) is a salient research topic in wireless systems, and
machine learning (ML) is emerging as a powerful tool for providing new data-driven security …

Artificial neural networks or neural networks (NN) are new computational models based on
the working of biological neurons of human body. A NN model consists of an interactive …

This paper proposes a feedback neural network model for solving convex nonlinear
programming (CNLP) problems. Under the condition that the objective function is convex …

This paper presents a dynamic optimization scheme for solving degenerate convex
quadratic programming (DCQP) problems. According to the saddle point theorem …

In this paper the application of projection neural network for solving bilinear programming
problems (BLPs) is obtained. So far as we know, no study has yet been attempted for these …

The shortest path problem is the classical combinatorial optimization problem arising in
numerous planning and designing contexts. This paper presents a neural network model for …

In this paper, we consider using the neural networks to efficiently solve the second-order
cone constrained variational inequality (SOCCVI) problem. More specifically, two kinds of …

This paper focuses on the computation issue of portfolio optimization with scenario-based
Value-at-Risk. The main idea is to replace the portfolio selection models with linear …

This paper presents a new neural network model for solving degenerate quadratic minimax
(DQM) problems. On the basis of the saddle point theorem, optimization theory, convex …

In this paper, a neural network model is constructed on the basis of the duality theory,
optimization theory, convex analysis theory, Lyapunov stability theory and LaSalle …