This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Northrop Grumman Systems Corporation. Active years: 2009.
Company Filing History:
Years Active: 2009
Title: The Innovative Mind of David H. Hoitsma
Introduction
David H. Hoitsma is an accomplished inventor based in Brentwood, NY (US). He has made significant contributions to the field of probability distribution methods through his innovative patent. His work is particularly relevant in the context of generating accurate predictions in various applications.
Latest Patents
David H. Hoitsma holds a patent for a "Prognosis adaptation method." This method involves generating a probability distribution for a desired variable. A hyperparameter density function is provided, from which values are randomly selected. The selected hyperparameter value is used to compute an input variable value. A value is randomly selected from each input variable probability density function. These values are input into a physics model to compute an output value. This process is repeated to generate numerous output values, which are then used to construct an output value probability density function. After constructing the output value probability density function, output value sensor data is obtained. The output density function is updated using the sensor data and a probabilistic evaluation of the hyperparameters. Improved predictions are iteratively made with the updated output distribution. This innovative approach has the potential to enhance predictive accuracy in various fields.
Career Highlights
David H. Hoitsma is associated with Northrop Grumman Systems Corporation, where he applies his expertise in developing advanced technologies. His work at this esteemed organization highlights his commitment to innovation and excellence in engineering.
Collaborations
David collaborates with Stephen J. Engel, leveraging their combined expertise to drive forward innovative projects and solutions.
Conclusion
David H. Hoitsma is a notable inventor whose work in probability distribution methods has significant implications for predictive modeling. His contributions continue to influence advancements in technology and engineering.