Now showing items 1-6 of 6
Target Discrimination with Neural Networks
The feasibility of distinguishing multiple type components of exo-atmospheric targets is demonstrated by applying the Time Delay Neural Network (TDNN) and the Adaptive Time-Delay Neural Network (ATNN). Exo-atmospheric ...
Commodity Trading Using Neural Networks: Models for the Gold Market
Essential to building a good financial forecasting model is having a realistic trading model to evaluate forecasting performance. Using gold trading as a platform for testing we present a profit based model which we use ...
Network Unfolding Algorithm and Universal Spatiotemporal Function Approximation
It has previously been known that a feed-forward network with time-delay can be unfolded into a conventional feed-forward network with a time history as input. In this paper, We show explicitly how this unfolding operation ...
Dynamic Attractors and Basin Class Capacity in Binary Neural Networks
The wide repertoire of attractors and basins of attraction that appear in dynamic neural networks not only serve as models of brain activity patterns but create possibilities for new computational paradigms that use ...
A Population-Based Search from Genetic Algorithms through Thermodynamic Operation
The guided random search techniques, genetic algorithms and simulated annealing, are very promising strategies, and both techniques are analogs from physical and biological systems. Through genetic algorithms, the simulation ...
Sampling Effects on Trajectory Learning and Production
The time-delay neural network (TDNN) and the adaptive time-delay neural network (ATNN) are effective tools for signal production and trajectory generation. Previous studies have shown production of circular and figure-eight ...