SEEK-TIME IMPROVEMENT IN A RANDOM-ACCESS FILE BY APPLICATION OF AN ADAPTIVE ELEMENT
Abstract
An Adaline (adaptive linear neuron) can be trained to distinguish between sets of inputs. In general, the quantized output is used. This report investigates the usefulness of the analog output of Adaline for measuring the frequency of occurrence of a number of different events. Each event is more or less arbitrarily associated with a pattern and it is shown that the degree to which Adaline has been trained to recognize any one of these patterns can be used as a measure of the frequency of occurrence of the associated event. The application of this use of Adaline to a random-access file is simulated in order to show its use in reducing average access time.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1963
- Accession Number
- AD0436020
Entities
People
- W. S. Buslik
Organizations
- Stanford University