Accession Number : ADA186213

Title :   Transient Classifier Systems and Man-Machine Interface Research.

Descriptive Note : Final technical rept. 8 Sep 86-7 Mar 87,

Corporate Author : PRESEARCH INC FAIRFAX VA

Personal Author(s) : Sax, Robert ; Kram, Richard

PDF Url : ADA186213

Report Date : 31 Aug 1987

Pagination or Media Count : 109

Abstract : The results of the experiment showed that transient detection and classification performance are highly independent, and both are very sensitive to signal-to-noise ratio (SNR). Unknown transients were recognized rapidly; however, performance at low SNR was not comparable to that against known transients. Transient specific syntax proved to be an even stronger determinant of performance than the known vs. unknown condition. Novice performance in detecting a target by its transient emissions was comparable to theoretical best current broadband techniques. Experienced sonar operators outperformed the novices by 12 dB. The automatic classification algorithm research demonstrated use of syntactic and semantic state variable feature-space representations to perform computationally efficient classification of transient patterns (50 times real-time in FORTRAN) and large-scale reduction of data (500:1). The algorithm recognized many singular and correlated transient events. An unexpected and exciting result was recognition and modal separation of mixed mode tonal signals as correlated transients in the time domain.

Descriptors :   *CLASSIFICATION, *ACOUSTIC DETECTION, ALGORITHMS, AUDIO TONES, AUTOMATION, BROADBAND, DATA REDUCTION, DETECTION, EMISSION, FORTRAN, INTERFACES, MAN MACHINE SYSTEMS, MULTIMODE, PATTERNS, SEPARATION, SIGNAL TO NOISE RATIO, SIGNALS, SONAR PERSONNEL, SYNTAX, TIME DOMAIN, TRANSIENTS, SOUND

Subject Categories : Acoustic Detection and Detectors

Distribution Statement : APPROVED FOR PUBLIC RELEASE