An Algorithm for Classification of Waveforms

For many applications the classification of structural similar sections within waveforms raises a lot of difficulties. Such sections, called ‘structur-units’, could represent typical signal shapes (e.g. the PQRST sequence in normal ECG) or some transient events (e.g. the K-complex in EEG during sleep). To recognize such structur-units one often uses syntactic techniques, which are sometimes combined with decision-theoretic methods for primitive assembly. Unfortunately the performance of this approach depends on the selection of meaningful primitives and often difficult grammars are required to master problems due to noise or distortion [1].