Researchers at North Carolina State University have developed a new analytical method that opens the door to faster processing of large amounts of information, with applications in fields as diverse as the military, medical diagnostics and homeland security.
"The problem we address here is this: When faced with a large amount of data, how do you determine which pieces of that information are relevant for solving a specific problem," says Dr. Joel Trussell, a professor of electrical and computer engineering at NC State and co-author of a paper describing the research. "For example, how would you select the smallest number of features that would allow a robot to differentiate between water and solid ground, based on visual data collected by video?"
This is important, because the more data you need to solve a problem, the more expensive it is to collect the data and the longer it will take to process the data. "The work we've done here allows for a more efficient collection of data by targeting exactly what information is most important to the decision-making process," Trussell says. "Basically, we've created a new algorithm that can be used to determine how much data is needed to make a decision with a minimal rate of error."