TRANSIENT ACOUSTIC ANALYSIS UTILIZING QUADRATIC SIGNAL REPRESENTATIONS AND NEUTRAL NETWORKS

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$59,221.00
Award Year:
1989
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Award Id:
9871
Agency Tracking Number:
9871
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
6811 Kenilworth Ave - Ste 306, Riverdale, MD, 20737
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Dr Joseph N Craig
(301) 927-3223
Business Contact:
() -
Research Institute:
n/a
Abstract
RECENT SOVIET ADVANCES IN ACOUSTIC QUIETING OF SUBMARINES IS PLACING INCREASED EMPHASIS ON THE EXPLOITATION OF PASSIVE INTERMITTENT AND TRANSIENT EMISSIONS. TRANSIENT SIGNALS CAN BE DESCRIBED EFFICIENTLY IN THE TIME--FREQUENCY PLANE USING THE WIGNER DISTRIBUTION OR IN THE CYCLIC SPECTRUM. BOTH OF THESE REPRESENTATIONS OFFER DISTINCT ADVANTAGES OVER SHORT-TIME FOURIER OR SPECTRAL ANALYSIS FOR TRANSIENT SIGNALS. NEURAL NETWORK TECHNOLOGY HAS EMERGED RECENTLY AS A PROMISING TOOL FOR BUILDING SIGNAL CLASSIFICATION SYSTEMS. NEURAL NETWORKS HAVE THE ABILITY TO GENERATE THE COMPLEX (AND OFTEN NONLINEAR) FEATURE TO SIGNAL CLASS MAPPINGS THAT ARE REQUIRED TO SOLVE ALL BUT THE SIMPLEST PROBLEMS. NEURAL NETWORKS ARE CAPABLE OF SELF ORGANIZATION TO CONSTRUCT DECISION FUNCTIONS, AND TO HAVE THE ABILITY TO LEARN ON-LINE. LNK PROPOSES TO USE QUADRATIC SIGNAL REPRESENTATIONS SUCH AS THE WIGNER DISTRIBUTION AND THE CYCLIC SPECTRUM TO PROVIDE INPUTS TO NEURAL NETWORKS THAT WILL CLASSIFY TRANSIENT SIGNALS TYPICAL OF THOSE ENCOUNTERED IN THE UNDERSEA ENVIRONMENT. THE OVERALL SYSTEM CONCEPTS AND TECHNIQUES WILL BE DEVELOPED AND TESTED IN PHASE I. A COMPLETE PROTOTYPE SYSTEM WILL BE DEVELOPED IN PHASE II.

* information listed above is at the time of submission.

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