Spiros Michalakopoulos

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An interesting problem in musicology is to classify songs according to rhythms. A rhythm is represented by a sequence of " Quick " (Q) and " Slow " (S) symbols, which correspond to the (relative) duration of notes, such that S = 2Q. Recently, Christodoulakis et al. [3] presented an efficient algorithm that can be used to classify musical texts according to(More)
A combinatorial model for analyzing and interpreting an electrocardiogram (ECG) was presented in [Allali et al. '10] and [Iliopoulos &#38; Michalakopoulos '09 and '10]. An application of the model is <i>QRS</i> peak detection and the resulting algorithm was shown to be space, as well as time efficient. Experimental results on the MIT-BIH Arrhythmia database(More)
Three problems that arise from electrocardiogram (ECG) interpretation and analysis are presented, followed by algorithmic solutions based on a combinatorial model. First, the beat classification problem is discussed and possible solutions are investigated. Secondly, given the R R-intervals, which can be determined using this combinatorial model, or any Q R(More)
Motivated by the identification of the musical structure of pop songs, we introduce combinatorial problems involving overlays (non-overlapping substrings) and the covering of a text t by them. We present 4 problems and suggest solutions based on string pattern matching techniques. We show that decision problems of this type can be solved using an(More)
An interesting problem in music information retrieval is to classify songs according to rhythms. A rhythm is represented by a sequence of “Quick” (Q) and “Slow” (S) symbols, which correspond to the (relative) duration of notes, such that S = 2Q. Christodoulakis et al. presented an efficient algorithm that can be used to classify musical sequences according(More)
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