Gerald H. Whipple

The use of programmed digital computers as general pattern classification and recognition devices is one phase of the current lively interest in artificial intelligence. It is important to choose a class of signals which is, at present, undergoing a good deal of visual inspection by trained people for the purpose of pattern recognition. In this way comparisons between machine and human performance may be obtained. A practical result also serves as additional motivation. Clinical electrocardiograms make up such a class of signals. The approach to the problem presented here centers upon the use of multiple adaptive matched filters that classify normalized signals. The present report gives some of the background for the application of this method.