SBIR/STTR Research Award
A Neural Network-Based Pilot-Aid for Rotorcraft Limit Avoidance
Award amount
$69,973Program and phase
SBIR · Phase IAward year
1995Award details
- Awarding agency
- Department of Defense
- Branch
- Army
- Recipient company
- OPTIMAL SYNTHESIS INC.
- Proposal award date
- Not reported
- Contract end date
- Not reported
- UEI
- REAUM5F2AM94
- Solicitation number
- Not reported
- Topic code
- Not reported
Research abstract
An innovative application of the pattern recognition technology for the development of a rotorcraft limit avoidance system is proposed. The system is based on a feature extraction algorithm and an artificial neural network. Feature extraction and pattern classification systems are designed using flight vehicle database and rotorcraft performance models. Display requirements and feasibility demonstration aspects of the project are also discussed.
Technology keywords
Not reported
Other awards by this recipient
Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.
- High-Performance Monte Carlo Modeling System for Real-time Fire Control Schedulers
- Human-Automation Speech Interface
- Human-Automation Speech Interface
- Tools for Implementing Speech Agents in Crew Resource Management Training Systems
- Fast Algorithms for Real-Time Hypervelocity Trajectory Adjustment
Research funding history
102 SBIR/STTR records share this UEI (1994–2020). Reported award amounts total $28,307,929. Reported amounts are not federal obligations.
Phases: Phase I, Phase II
Agencies: National Aeronautics and Space Administration, Department of Defense