A Self-Designing Intelligent Signal Processing System Capable of Evolutional Learning for Classification/Recognition of One and Multidimensional Signals is described which classifies data by an evolutionary learning environment that develops the features and algorithms that are best suited for the recognition problem under consideration. The System adaptively learns what data need to be extracted in order to recognize the given pattern with the least amount of processing. The System decides what features need to be selected for classification and/or recognition to fit a certain structure that leads to the least amount of processing according to the nature of the given data. The System disclosed herein is capable of recognizing an enormously large number of patterns with a high accuracy.
US 7,016,885 B1
Application Serial Number
Assignee at Issuance
College of Engineering and Computer Science (CECS)
Electrical Engineering & Computer Science - CS Division
Assignee at Filing
Nonprovisional Application Record
Mikhael, Wasfy; Abdelwahab, Manal; and Krishnan, Venkatesh, "Self Designing Intelligent Signal Processing System capable of evolutional Learning for Classification/Recognition of One and Multidimensional Signals" (2006). UCF Patents. 505.