In nuclear fission, a delayed neutron is a neutron emitted by one of the fission products any time from a few milliseconds to a few minutes after the fission event. The counts of delayed neutrons constitute a time series sequence. The analysis of such time series can prove to be very significant for purpose of predictive maintenance in nuclear power plants. In this paper we aim to identify anom...

This paper deals with symbolic time series representation. It builds up on the popular mapping technique Symbolic Aggregate approXimation algorithm (SAX), which is extensively utilized in sequence classification, pattern mining, anomaly detection, indexing and other data mining tasks. However, disadvantage of this method is, that it works reliably only for Gaussian-like distribution. In our pre...

This paper presents a novel method for loop optimization that exploits symbolic evaluation of chains of recurrences (CRs). The method generalizes loop induction expression recognition, loop parallelization by induction variable substitution, loop strength reduction , and loop invariant expression elimination (code motion). Symbolic diierencing of loops has been extensively studied by Haghighat ...

Sequence processing involves several tasks such as clustering, classification, prediction, and transduction of sequential data which can be symbolic, non-symbolic or mixed. Examples of symbolic data patterns occur in modelling natural (human) language, while the prediction of water level of River Thames is an example of processing non-symbolic data. If the content of a sequence will be varying ...

Similarity search is a fundamental problem in information technology. The main difficulty of this problem is the high dimensionality of the data objects. In large time series databases, it’s important to reduce the dimensionality of these data objects, so that we can manage them. Symbolic representation is a promising technique of dimensionality reduction. In this paper we propose a new distanc...