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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. METHODS FOR REDUCING PLASMA EFFECTS ON THE NASP

    SBC: ACCURATE AUTOMATION CORPORATION            Topic: N/A

    WE PROPOSE THE DEVELOPMENT OF AN INNOVATIVE NEUROCONTROLLER THAT GENERATES TRAJECTORIES WHICH REDUCE PLASMA EFFECTS ON THE COMMUNICATION SYSTEM OF THE NASP. WE WILL MODEL PLASMA SHEATH GENERATION AND INCORPORATE THIS MODEL INTO A GHAME FLIGHT SIMULATOR ON A SILICON GRAPHICS WORKSTATION. THIS MODEL WILL THEN BE USED IN THE DEVELOPMENT OF THE CONTROLLER AND SUITABLE ADAPTATION LAWS. COST FUNCTIONS W ...

    SBIR Phase II 1993 Department of DefenseAir Force
  2. PARALLEL NEURAL NETWORK TOOLBOX FOR SUPERCOMPUTERS

    SBC: ACCURATE AUTOMATION CORPORATION            Topic: N/A

    THIS PROPOSAL INVOLVES RESEARCH INTO A SUPERCOMPUTER-BASED ENVIRONMENT FOR RESEARCH INTO MASSIVELY PARALLEL NEURAL-NETWORK ALGORITHMS FOR LARGE SCALE, COMPUTATIONALLY INTENSE PROBLEMS. THIS ENVIRONMENT WILL HAVE APPLICATION TO AREAS SUCH AS IMAGE PROCESSING, PATTERN RECOGNITION, CONTROL SIGNAL PROCESSING, DATA COMPRESSION, AND FAULT DIAGNOSIS. ALL OF THESE ARE AREAS WHICH INVOLVE MASSIVE AMOUNTS O ...

    SBIR Phase II 1993 Department of DefenseAir Force
  3. Ontogenic Neural Networks for Avionics Applications

    SBC: ACCURATE AUTOMATION CORPORATION            Topic: N/A

    The study of neural networks which possess the capability to learn and grow with little or no supervision will be explored during this research effort. These networks exhibit ontogenic behavior and are termed ontogenic neural networks. This reasearch effort explores the use of hybrid neural network structures which are capable of self-organization, feature discovery and self generation in a compos ...

    SBIR Phase I 1993 Department of DefenseAir Force
  4. NEURAL NETWORKS, YOULA PARAMETERIZATION AND RECONFIGURABLE CONTROL SYSTEM

    SBC: ACCURATE AUTOMATION CORPORATION            Topic: N/A

    N/A

    SBIR Phase I 1993 National Science Foundation
  5. Aircraft and Cruise Missile Mission and Route Planning in Near Real-time

    SBC: ACCURATE AUTOMATION CORPORATION            Topic: N/A

    N/A

    SBIR Phase I 1993 Department of DefenseNavy
  6. Neural Network Methods for Preventing Unstarts

    SBC: ACCURATE AUTOMATION CORPORATION            Topic: N/A

    N/A

    SBIR Phase I 1993 Department of DefenseAir Force
  7. Sensor Fusion in a Dynamic Model-Based System

    SBC: ACCURATE AUTOMATION CORPORATION            Topic: N/A

    N/A

    SBIR Phase I 1993 Department of DefenseAir Force
  8. Precision Programmable Direct Injection, Monitoring and Reporting System

    SBC: Ag Systems, Inc.            Topic: N/A

    N/A

    SBIR Phase I 1993 Department of Agriculture
  9. Helicopter Tail Rotor Gearbox Fault Detector

    SBC: American Joining Institute            Topic: N/A

    N/A

    SBIR Phase I 1993 Department of DefenseNavy
  10. Improved Temperature Measurement in Composite Material for Aerospace Applications

    SBC: ANALYSIS AND MEASUREMENT SERVICE CORPORATION            Topic: N/A

    N/A

    SBIR Phase I 1993 National Aeronautics and Space Administration
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