Electrical motor stator current signals have been widely used to monitor the condition of induction machines and their downstream mechanical equipment. The key technique used for current signal analysis is based on Fourier transform (FT) to extract weak fault sideband components from signals predominated with supply frequency component and its higher order harmonics. However, the FT based metho...

Developing handwriting recognition systems that are fast and highly reliable is a challenging problem that has become increasingly relevant following the broad acceptance of hand-held devices that use pen based handwriting inputs. Generative classifiers offer a promising solution in combination with discriminative classifiers for addressing this challenge. This paper describes a novel generativ...

We propose novel approaches to cast the widely-used family of Dynamic Time Warping (DTW) distances and similarities as positive definite kernels for time series. To this effect, we provide new theoretical insights on the family of Global Alignment kernels introduced by Cuturi et al. (2007) and propose alternative kernels which are both positive definite and faster to compute. We provide experim...

Fungal infections are a global problem imposing considerable disease burden. One of the unmet needs in addressing these infections is rapid, sensitive diagnostics. A promising molecular diagnostic approach is high-resolution melt analysis (HRM). However, there has been little effort in leveraging HRM data for automated, objective identification of fungal species. The purpose of these studies wa...

Temporal data are naturally everywhere, especially in the digital era that sees the advent of big data and internet of things. One major challenge that arises during temporal data analysis and mining is the comparison of time series or sequences, which requires to determine a proper distance or (dis)similarity measure. In this context, the Dynamic Time Warping (DTW) has enjoyed success in many ...

The performance of two techniques is compared for automated recognition of bird song units from continuous recordings. The advantages and limitations of dynamic time warping (DTW) and hidden Markov models (HMMs) are evaluated on a large database of male songs of zebra finches (Taeniopygia guttata) and indigo buntings (Passerina cyanea), which have different types of vocalizations and have been ...

Time-series classification has gained wide attention within the Machine Learning community, due to its large range of applicability varying from medical diagnosis, financial markets, up to shape and trajectory classification. The current state-of-art methods applied in timeseries classification rely on detecting similar instances through neighboring algorithms. Dynamic Time Warping (DTW) is a s...

Poor handwriting is a diagnostic criterion for developmental coordination disorder. Typical of poor handwriting is its low overall quality and the high variability of the spatial characteristics of the letters, usually assessed with a subjective handwriting scale. Recently, Dynamic Time Warping (DTW), a technique originally developed for speech recognition, was introduced for pattern recognitio...

Spoken term detection is important for retrieval of multimedia and spoken content over the Internet. Because it is difficult to have acoustic/language models well matched to the huge quantities of spoken documents produced under various conditions, unsupervised approaches using frame-based dynamic time warping (DTW) has been proposed to compare the spoken query with spoken documents frame by fr...

0957-4174/$ see front matter 2012 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2012.05.012 ⇑ Corresponding author. Tel.: +36 88 624209. E-mail address: [email protected] (J. Ab In recent years, dynamic time warping (DTW) has begun to become the most widely used technique for comparison of time series data where extensive a priori knowledge is not available. However, it is often expe...