About Martingale Research Corporation
Meeting the needs of our clients means spending the time to understand their challenges, develop "real-world" solutions, and implement effective results. We are committed to actively maintaining an open dialogue with each client to ensure that they attain their vision.
Martingale Research Corporation was incorporated in 1986 for the purpose of advancing the state of the art in intelligent computing, particularly the research and development of neural networks. Since our inception, we have never lost sight of our original goal, which was to apply advanced computing concepts to real-world problems. Our clients include a variety of U.S. Government agencies (Martingale Research client list), and their sponsorship has allowed us to develop and deploy innovative solutions to some very tough problems in adaptive controls, image processing, speech recognition, and database exploitation.
The company has been active in the Small Business Innovation Research (SBIR) program since our beginnings. Through multiple SBIR contracts, we have developed a concept and a computing architecture for intelligent pattern recognition based on the theory of Quantum Neurodynamics. QND models large system interactions in terms of mathematical functions and concepts adapted from the fields of sub-atomic physics. The architectural realization of the QND theory is the Parametric Avalanche Stochastic Filter (PASF). The PASF neural network is designed to be able to process nonlinear, temporally changing, highly dynamic systems and signals. The PASF has been applied to problems as widely disparate as controlling the pointing angle of a tank gun and recognizing continuous speech in a high noise environment. Patent filings have been executed in the U.S., Japan, Australia, and the European Community. Martingale Research Corporation retains all commercial rights to the PASF, and has executed a government-use license to the United States in accordance with requirements of the SBIR program.
More recent efforts have focused on deploying to the marketplace the fundamental technologies developed during our early years. We are developing a new method for real-time detection of metal/composite material fatigue growth. This technology has wide applicability, particularly in the aerospace industry and for the national transportation infrastructure. We have also developed a system for interactive exploitation of hidden data relationships (data mining) in large or small databases. This technology has applications ranging from health care industries to insurance risk assessment to targeted consumer marketing.
Over the last few years, our focus has shifted to developing advanced statistical analysis methods that allow more useful and accurate information to be obtained from real-world datasets. We have continued to participate in the SBIR program, and have been working with the National Institute on Alcohol Abuse and Alcoholism (NIAAA), as well as other health-related organizations, to address the weaknesses in traditional statistical analysis performed on real-world data.Skip to navigation