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A Parallel Adaptive Wavelet Processor for Realtime Pattern Recognition…

Award Information

Agency:
Department of Defense
Branch:
Army
Award ID:
28883
Program Year/Program:
1996 / SBIR
Agency Tracking Number:
28883
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
LNK CORP., INC.
6811 Kenilworth Avenue, Suite 306 Riverdale, MD 20737
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Woman-Owned: No
Minority-Owned: Yes
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 1996
Title: A Parallel Adaptive Wavelet Processor for Realtime Pattern Recognition Applications
Agency / Branch: DOD / ARMY
Contract: N/A
Award Amount: $599,997.00
 

Abstract:

Wavelet transforms have already proved to be very useful tools in many signal processing applications including digital audio and video compression. Although the wavelet-based representations offer more versatility in time-frequency localization than other Fourier methods, they tend to have poor localization especially near high frequencies. To eliminate this difficulty, we propose a technique for analyzing signals of time-varying characteristics using adaptive wavelet packets, which facilitates identification of arbitrarily localized spectral characteristics. For nonstationary signals that contain varying distribution of spectral energy, the analysis must adaptively select filters of different localization properties. Wavelet-packets designed through digital filter banks offer arbitrary tiling of the time-frequency domain. Herley et al. [1993] report a double-tree algorithm that combines selection for the best wavelet-packet expansion with an adaptive time-segmentation of the signal simultaneously. The system we propose here is an extension of the above algorithm together with a choice of a basis function from a library of wavelet packets. We also propose to develop the pattern recognition capabilities based on feature vectors computed from the compressed signals. A real-time prototype wavelet transform processor will be available in Phase II on an inexpensive parallel hardware called PC - CNAPS that operates as an accelerator board to a PC.

Principal Investigator:

Dr. Srinivasan Raghavan
3019273223

Business Contact:

Small Business Information at Submission:

Lnk Corp, Inc.
6811 Kenilworth Ave., Ste. 306 Riverdale, MD 20737

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