Though the concept of sample mean in dynamic time warping (DTW) spaces is used in pattern recognition applications, its existence has neither been proved nor called into question. This article shows that a sample mean exists under general conditions that cover common variations of different DTW-spaces mentioned in the literature. The existence proofs are based on a Reduction Theorem that bounds...

The Dynamic Time Warping (DTW) is a popular similarity measure between time series. The DTW fails to satisfy the triangle inequality and its computation requires quadratic time. Hence, to find closest neighbors quickly, we use bounding techniques. We can avoid most DTW computations with an inexpensive lower bound (LB Keogh). We compare LB Keogh with a tighter lower bound (LB Improved). We find ...

Wrist pulse analysis for identification of health status is found in Ancient Indian as well as Chinese literature. The preprocessing of wrist pulse is necessary to remove outlier pulses and fluctuations prior to the analysis of pulse pressure signal. This paper discusses the identification of irregular pulses present in the pulse series and intricacies associated with the extraction of time dom...

For power suppliers, an important task is to accurately predict the short-term load. Thus many papers have introduced different kinds of artificial intelligent models to improve the prediction accuracy. In recent years, Random Forest Regression (RFR) and Support Vector Machine (SVM) are widely used for this purpose. However, they can not perform well when the sample data set is too noisy or wit...

This paper presents a procedure of frame normalization based on the traditional dynamic time warping (DTW) using the LPC coefficients. The redefined method is called as the DTW frame-fixing method (DTW-FF), it works by normalizing the word frames of the input against the reference frames. The enthusiasm to this study is due to neural network limitation that entails a fix number of input nodes f...

Non-invasive spatial activity recognition is a difficult task, complicated by variation in how the same activities are conducted and furthermore by noise introduced by video tracking procedures. In this paper we propose an algorithm based on dynamic time warping (DTW) as a viable method with which to quantify segmented spatial activity sequences from a video tracking system. DTW is a widely use...

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...

We propose in this paper a differentiable learning loss between time series, building upon the celebrated dynamic time warping (DTW) discrepancy. Unlike the Euclidean distance, DTW can compare time series of variable size and is robust to shifts or dilatations across the time dimension. To compute DTW, one typically solves a minimal-cost alignment problem between two time series using dynamic p...

The XWand is a wireless UI device that enables styles of natural interaction with intelligent environments. The XWand system exploits human intuition, allowing control of everyday objects through pointing and gesturing. We describe the hardware device and then examine several approaches to gesture recognition. We discuss results from experiments using a linear time warping method, a dynamic tim...

We present an algorithm for Dynamic Time Warping (DTW) on multi-dimensional time series (MDDTW). The algorithm utilises all dimensions to find the best synchronisation. It is compared to ordinary DTW, where a single dimension is used for aligning the series. Both one-dimensional and multidimensional DTW are also tested when derivatives instead of feature values are used for calculating the warp...