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SBIR-STTR Award
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SBIR-STTR Award
10
Robust Morphologically Based Sampling For Ann
Award last edited on: 5/16/2002
Sponsored Program
SBIR
Awarding Agency
DOD : Army
Total Award Amount
$49,960
Award Phase
1
Solicitation Topic Code
A90-195
Principal Investigator
Harold Longbotham
Company Information
BBL Research Inc
111 Villa Ann
San Antonio, TX 78213
(512) 691-5518
N/A
N/A
Location:
Single
Congr. District:
21
County:
Bexar
Phase I
Contract Number:
39640
Start Date:
00/00/00
Completed:
00/00/00
Phase I year
1990
Phase I Amount
$49,960
The problem of interest is to improve pattern recognition techniques by decreasing the training time for artificial neural networks (ann) and increasing the robutness of the recall of ann. We propose to decrease training time by introducing morphologically based recon- figurable sampling arrays. We will increase the fault tolerance or robustness of object detection tasks by introducing a hybird model that incorporates robust filtering prior to the ann input. There are two problems in this area we would like to investigate. An obvious step in decreasing training time is to reduce the number of inputs and therefore the number of interconnects. We will investi- gate the effectiveness of the interconnection of sensors on morphological "shaping" considerations and prior knowledge of the object of interest. The second problem we wish to investigate is an increase in the robutness of anns for both impulsive noise and varying sensor output amplitudes due to varying input intensities. We will examine impulsive noise via the use of order statistic (os) filters such as the median after an morphologically based interconntection of the sensors. We will approach the problem of varying intensities by renormalization of the inputs from the morphologically selected set of sensors to the ann.
Keywords:
Phase II
Contract Number:
----------
Start Date:
00/00/00
Completed:
00/00/00
Phase II year
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Phase II Amount
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