Recurrent Neural Network Classifier for Three Layer Conceptual Network and Performance Evaluation

An efficient one-layer recurrent neural network for solving a class of nonsmooth optimization problems

Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subject to nonlinear inequality and affine equality constraints. It is a one-layer non-penalty recurrent neural network based on the...

A novel two-layer neural network classifier

A Recurrent Neural Network Model for Solving Linear Semidefinite Programming

In this paper we solve a wide rang of Semidefinite Programming (SDP) Problem by using Recurrent Neural Networks (RNNs). SDP is an important numerical tool for analysis and synthesis in systems and control theory. First we reformulate the problem to a linear programming problem, second we reformulate it to a first order system of ordinary differential equations. Then a recurrent neural network...

Conceptual Multi-layer Neural Network Model for Headline Generation

Neural attention-based models have been widely used recently in headline generation by mapping source document to target headline. However, the traditional neural headline generation models utilize the first sentence of the document as the training input while ignoring the impact of the document concept information on headline generation. In this work, A new neural attention-based model called ...

Performance Evaluation of Neural Network

Embedded systems need to respect stringent real time constraints. Various hardware components included in such systems such as cache memories exhibit variability and therefore affect execution time. Indeed, a cache memory access from an embedded microprocessor might result in a cache hit where the data is available or a cache miss and the data need to be fetched with an additional delay from an...