Learning-Based Source Separation Methodologies Applicable to the Multiple Target Problem

Award Information
Agency: Department of Defense
Branch: Army
Contract: DAAE30-02-C-1064
Agency Tracking Number: A012-1935
Amount: $70,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2002
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
P.O. Box 2010, Pawtucket, RI, 02861
DUNS: 036339534
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jose Lopez
 CEO
 (508) 229-3390
 lopez@coprime.com
Business Contact
 Jose Lopez
Title: CEO
Phone: (508) 229-3390
Email: lopez@coprime.com
Research Institution
N/A
Abstract
"Coprime proposes to investigate the applicability of learning-based source separation methodologies to the problem of multiple targets in a complex acoustic environment. The Phase I effort will focus on identifying viable learning-based source separationalgorithms specifically tuned to the multiple combat vehicle scenario. A prototype architecture will be developed and numerical software rapidly developed in order to test the performance of the learning-based algorithms developed on multiple combatvehicle data sets. Coprime proprietary Vehicle Signal Analysis Environment and Vehicle Monitor Simulation Environment will be employed to assist in evaluating the performance of the learning-based source separation algorithms developed under this Phase I.Anticipated benefits include robust, low cost, software-based, modular algorithms that can be rapidly integrated into a wide variety of passive, acoustic monitors used in sophisticated surveillance systems."

* Information listed above is at the time of submission. *

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