Accession Number:

ADA279148

Title:

The Use of Fuzzy Set Classification for Pattern Recognition of the Polygraph

Descriptive Note:

Final rept. 15 Jan-31 Dec 1993

Corporate Author:

SAN JOSE STATE UNIV CA

Personal Author(s):

• Knapp, Benjamin
• Dastmalchi, Mitra
• Jacobs, Eric
• Layeghi, Shahab

Report Date:

1993-12-01

Pagination or Media Count:

230.0

Abstract:

Polygraph tests are a widely used method to distinguish between truth, and deception. Polygraph charts are usually analyzed by human interpreters. However, computer algorithms are now being developed to score the tests or verify the results. These methods are based on statistical classification techniques. In this study a number of time, frequency and correlation domain features were selected and used. The fuzzy K-nearest neighbor algorithm was used to classify the polygraph charts, a correct classification of ninety-one percent was obtained for a set of one hundred case files supplied by the NSA.

Descriptors:

• *PATTERN RECOGNITION
• *FUZZY SETS
• *LIE DETECTORS
• TEST AND EVALUATION
• ALGORITHMS
• FREQUENCY
• HUMANS
• DECEPTION
• INTERPRETERS
• CHARTS
• COMPUTERS
• TIME
• CORRELATION
• CLASSIFICATION

Subject Categories:

• Psychology
• Theoretical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE