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COMPUTERIZED SCHEDULED GRADUAL REDUCTION FOR SMOKING

Award Information

Agency:
Department of Health and Human Services 		Branch:
N/A 		Award ID:
45737 		Program Year/Program:
1999 / SBIR
Agency Tracking Number:
1R43CA083451-01 		Solicitation Year:
N/A 		Solicitation Topic Code:
N/A 		Solicitation Number:
N/A
Small Business Information
PERSONAL IMPROVEMENT COMPUTER SYSTEMS
12007 SUNRISE VALLEY DR, STE 480 RESTON, VA 22091-
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 1999
Title: COMPUTERIZED SCHEDULED GRADUAL REDUCTION FOR SMOKING
Agency: HHS
Contract: N/A
Award Amount: $99,836.00
 

Abstract:

Not Available A set of advanced broadband processing algorithms and a broadband classifier are being proposed for clutter rejection and detection/classification of weak targets in sonobuoy returns. Novel algorithms for the harsh shallow water acoustic environment are needed since the threat model for the ASW has shifted from deep to shallow water. Recent efforts by the underwater community have identified the advantages of using broadband signals and new processing techniques to limit the effects of reverberation. This effort proposes an unconventional approach that exploits the broadband nature of explosive or impulse-like sources, as well as the new generation of coherent broadband acoustic sources the Navy uses. This broadband approach achieves very good array gain and dynamic range using a limited number of sensors. This technique uses degrees of freedom in the frequency domain, by drawing an analogy with degrees of freedom in space in a discrete line-array. The algorithms being proposed include broadband adaptive filtering, beam canceling and modified eigen-vector beamforming techniques. These algorithms are used to feed a broadband classifier based on a time/frequency wavelet analysis, and are expected to enhance the performance of future ASW systems operating in high clutter environments.

Principal Investigator:

Neal R. Boyd

Business Contact:


7037581400
ALBEHAR@LIFESIGN.COM
Small Business Information at Submission:

PERSONAL IMPROVEMNT COMPUTER SYS
12007 SUNRISE VALLEY DR, STE 480 RESTON, VA 22091

EIN/Tax ID: 541657983
DUNS: N/A
Number of Employees: N/A
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No