Search results for "dynamic time warping"

CUDA-Accelerated Alignment of Subsequences in Streamed Time Series Data

2014

Euclidean Distance (ED) and Dynamic Time Warping (DTW) are cornerstones in the field of time series data mining. Many high-level algorithms like kNN-classification, clustering or anomaly detection make excessive use of these distance measures as subroutines. Furthermore, the vast growth of recorded data produced by automated monitoring systems or integrated sensors establishes the need for efficient implementations. In this paper, we introduce linear memory parallelization schemes for the alignment of a given query Q in a stream of time series data S for both ED and DTW using CUDA-enabled accelerators. The ED parallelization features a log-linear calculation scheme in contrast to the naive …

Alignments of Time Intensity curves in sensory analysis

2006

International audience

2015

Alternative splicing is an important mechanism in eukaryotes that expands the transcriptome and proteome significantly. It plays an important role in a number of biological processes. Understanding its regulation is hence an important challenge. Recently, increasing evidence has been collected that supports an involvement of intragenic DNA methylation in the regulation of alternative splicing. The exact mechanisms of regulation, however, are largely unknown, and speculated to be complex: different methylation profiles might exist, each of which could be associated with a different regulation mechanism. We present a computational technique that is able to determine such stable methylation pa…

Cruise passengers' trajectories at destination. A Dynamic Time Warping approach.

2015

The present work aims at proposing an analysis of cruise passengers trajectories at the destination through Dynamic Time Warping algorithm. Data collected through GPS devices on cruise passengers’ behavior in the port of Palermo are analyzed in order to show similarities and differences among their spatial trajectories at the destination. A cluster analysis is performed in order to identify cruise passengers’ segments based on trajectories’ similarity. Results are of interest from both a methodological perspective related with the analysis of GPS data, and for the management and planning of cruise tourism destinations.

GEM

2014

The widespread use of digital sensor systems causes a tremendous demand for high-quality time series analysis tools. In this domain the majority of data mining algorithms relies on established distance measures like Dynamic Time Warping (DTW) or Euclidean distance (ED). However, the notion of similarity induced by ED and DTW may lead to unsatisfactory clusterings. In order to address this shortcoming we introduce the Gliding Elastic Match (GEM) algorithm. It determines an optimal local similarity measure of a query time series Q and a subject time series S. The measure is invariant under both local deformation on the measurement-axis and scaling in the time domain. GEM is compared to ED and…

Exploiting Correlation between Body Gestures and Spoken Sentences for Real-time Emotion Recognition

2017

Humans communicate their affective states through different media, both verbal and non-verbal, often used at the same time. The knowledge of the emotional state plays a key role to provide personalized and context-related information and services. This is the main reason why several algorithms have been proposed in the last few years for the automatic emotion recognition. In this work we exploit the correlation between one's affective state and the simultaneous body expressions in terms of speech and gestures. Here we propose a system for real-time emotion recognition from gestures. In a first step, the system builds a trusted dataset of association pairs (motion data -> emotion pattern), a…

Assessing the predictability of Medicanes in ECMWF ensemble forecasts using an object-based approach

2018

The predictability of eight southern European tropical-like cyclones, seven of which Medicanes, is studied evaluating ECMWF operational ensemble forecasts against operational analysis data. Forecast cyclone trajectories are compared to the cyclone trajectory in the analysis by means of a dynamic time warping technique, which allows to find a match in terms of their overall spatio-temporal similarity. Each storm is treated as an object and its forecasts are analysed using metrics that describe intensity, symmetry, compactness, and upper-level thermal structure. This object-based approach allows to focus on specific storm features, while tolerating their shifts in time and space to some exten…

Vector representation of non-standard spellings using dynamic time warping and a denoising autoencoder

2017

The presence of non-standard spellings in Twitter causes challenges for many natural language processing tasks. Traditional approaches mainly regard the problem as a translation, spell checking, or speech recognition problem. This paper proposes a method that represents the stochastic relationship between words and their non-standard versions in real vectors. The method uses dynamic time warping to preprocess the non-standard spellings and autoencoder to derive the vector representation. The derived vectors encode word patterns and the Euclidean distance between the vectors represents a distance in the word space that challenges the prevailing edit distance. After training the autoencoder o…

An EEMD Aided Comparison of Time Histories and Its Application in Vehicle Safety

2017

In the context of signal processing, the comparison of time histories is required for different purposes, especially for the model validation of vehicle safety. Most of the existing metrics focus on the mathematical value only. Therefore, they suffer the measuring errors, disturbance, and uncertainties and can hardly achieve a stable result with a clear physical interpretation. This paper proposes a novel scheme of time histories comparison to be used in vehicle safety analysis. More specifically, each signal for comparison is decomposed into a trend signal and several intrinsic mode functions (IMFs) by ensemble empirical mode decomposition. The trend signals reflect the general variation a…

On the use of a metric-space search algorithm (AESA) for fast DTW-based recognition of isolated words

1988

The approximating and eliminating search algorithm (AESA) presented was recently introduced for finding nearest neighbors in metric spaces. Although the AESA was originally developed for reducing the time complexity of dynamic time-warping isolated word recognition (DTW-IWR), only rather limited experiments had been previously carried out to check its performance in this task. A set of experiments aimed at filling this gap is reported. The main results show that the important features reflected in previous simulation experiments are also true for real speech samples. With single-speaker dictionaries of up to 200 words, and for most of the different speech parameterizations, local metrics, a…