Radio Frequency Machine Learning Systems (RFMLS)
Closed Solicitation Posted
- Solicitation number
- HR001117S0043
- Agency
-
Defense Advanced Research Projects Agency
Department of Defense
- Responses due
- Set-aside
- No set-aside
Opportunity facts
- Contract number
- FA875018C0111 Federal contract award
- NAICS code
- 541712 Research and Development in the Physical, Engineering, and Life Sciences (except Biotechnology)
- PSC
- Not on record
Notice details come from SAM.gov. Updated .
Notice text
3 versions
Update #3 · Latest ·
Amendment 02: The purpose of this amendment is to correct typos in Amendment 01 regarding the proposal submission due date as highlighted in yellow in the attached BAA document.
Amendment 01: The purpose of this amendment is to revise the BAA in accordance with responses to the posted FAQ.
Original Synopsis Below.
The goal of the RF Machine Learning Systems (RFMLS) program is to develop the foundations for applying modern data-driven Machine Learning to the RF Spectrum domain as well as to develop practical applications in emerging spectrum problems which demand vastly improved discrimination performance over today's hand-engineered RF systems. Ultimately these innovations will result in a new generation of RF systems that are goal-driven and can learn from data rather than being hand-engineered by experts.
Update #2 ·
Amendment 01: The purpose of this amendment is to revise the BAA in accordance with responses to the posted FAQ.
Original Synopsis Below.
The goal of the RF Machine Learning Systems (RFMLS) program is to develop the foundations for applying modern data-driven Machine Learning to the RF Spectrum domain as well as to develop practical applications in emerging spectrum problems which demand vastly improved discrimination performance over today's hand-engineered RF systems. Ultimately these innovations will result in a new generation of RF systems that are goal-driven and can learn from data rather than being hand-engineered by experts.
Update #1 ·
The goal of the RF Machine Learning Systems (RFMLS) program is to develop the foundations for applying modern data-driven Machine Learning to the RF Spectrum domain as well as to develop practical applications in emerging spectrum problems which demand vastly improved discrimination performance over today's hand-engineered RF systems. Ultimately these innovations will result in a new generation of RF systems that are goal-driven and can learn from data rather than being hand-engineered by experts.
Files
| File | Type | Posted |
|---|---|---|
| HR001117S0043-Amendment-01.pdf | ||
| HR001117S0043.pdf | ||
| HR001117S0043_RFMLS_Attachment1_ProposerChecklist.pdf | ||
| HR001117S0043_RFMLS_Attachment2_ProposalSummaryChartTemplate.pptx | PPTX presentation |
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