Now showing items 1-6 of 6
Learning with the Adaptive Time-Delay Neural Network
The Adaptive Time-delay Neural Network (AT N N), a paradigm for training a nonlinear neural network with adaptive time-delays, is described. Both time delays and connection weights are adapted on-line according to a gradient ...
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 ...
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 Learning Algorithm for Adaptive Time-Delays in a Temporal Neural Network
The time delay neural network (TDNN) is an effective tool for speech recognition and spatiotemporal classification. This network learns by example, adapts its weights according to gradient descent, and incorporates a time ...
Fast Gravity: An n-Squared Algorithm for Identification of Synchronous Neural Assemblies
The identification of synchronously active neural assemblies in simultaneous recordings of neuron activities is an important research issue and a difficult algorithmic problem. A gravitational analysis method was developed ...