Patsnap Eureka AI that helps you search prior art, draft patents, and assess FTO risks, powered by patent and scientific literature data.
34 results about "Source separation" patented technology
Filter
Efficacy Topic
Property
Owner
Technical Advancement
Application Domain
Technology Topic
Technology Field Word
Patent Country/Region
Patent Type
Patent Status
Application Year
Inventor
Source separation problems in digital signal processing are those in which several signals have been mixed together into a combined signal and the objective is to recover the original component signals from the combined signal. The classical example of a source separation problem is the cocktail party problem, where a number of people are talking simultaneously in a room, and a listener is trying to follow one of the discussions. The human brain can handle this sort of auditory source separation problem, but it is a difficult problem in digital signal processing. This was first analyzed by Colin Cherry. Several approaches have been proposed for the solution of this problem but development is currently still very much in progress. Some of the more successful approaches are principal components analysis and independent components analysis, which work well when there are no delays or echoes present; that is, the problem is simplified a great deal. The field of computational auditory scene analysis attempts to achieve auditory source separation using an approach that is based on human hearing. The human brain must also solve this problem in real time.