Search results for "dynamic time warping"
showing 10 items of 21 documents
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…
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 …
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…
Measuring Dissimilarity Between Curves by Means of Their Granulometric Size Distributions
2008
The choice of a dissimilarity measure between curves is a key point for clustering functional data. Functions are usually pointwise compared and, in many situations, this approach is not appropriate. Mathematical Morphology provides us with a toolbox to overcome this problem. We propose some dissimilarity measures based on morphological granulometries and their performance is evaluated on some functional datasets.
Alignment of Noisy and Uniformly Scaled Time Series
2009
The alignment of noisy and uniformly scaled time series is an important but difficult task. Given two time series, one of which is a uniformly stretched subsequence of the other, we want to determine the stretching factor and the offset of the second time series within the first one. We adapted and enhanced different methods to address this problem: classical FFT-based approaches to determine the offset combined with a naive search for the stretching factor or its direct computation in the frequency domain, bounded dynamic time warping and a new approach called shotgun analysis, which is inspired by sequencing and reassembling of genomes in bioinformatics. We thoroughly examined the strengt…
Introducing the Temporal Distortion Index to perform a bidimensional analysis of renewable energy forecast
2016
Abstract Wind has been the largest contributor to the growth of renewal energy during the early 21st century. However, the natural uncertainty that arises in assessing the wind resource implies the occurrence of wind power forecasting errors which perform a considerable role in the impacts and costs in the wind energy integration and its commercialization. The main goal of this paper is to provide a deeper insight in the analysis of timing errors which leads to the proposal of a new methodology for its control and measure. A new methodology, based on Dynamic Time Warping, is proposed to be considered in the estimation of accuracy as attribute of forecast quality. A new dissimilarity measure…
A Novel Time Series Kernel for Sequences Generated by LTI Systems
2017
The recent introduction of Hankelets to describe time series relies on the assumption that the time series has been generated by a vector autoregressive model (VAR) of order p. The success of Hankelet-based time series representations prevalently in nearest neighbor classifiers poses questions about if and how this representation can be used in kernel machines without the usual adoption of mid-level representations (such as codebook-based representations). It is also of interest to investigate how this representation relates to probabilistic approaches for time series modeling, and which characteristics of the VAR model a Hankelet can capture. This paper aims at filling these gaps by: deriv…
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…
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.
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…