An indoor fusion navigation algorithm using HV-derivative dynamic time warping and the chicken particle filter

Derivative Dynamic Time Warping

Time series are a ubiquitous form of data occurring in virtually every scientific discipline. A common task with time series data is comparing one sequence with another. In some domains a very simple distance measure, such as Euclidean distance will suffice. However, it is often the case that two sequences have the approximately the same overall component shapes, but these shapes do not line up...

Map-Based Indoor Pedestrian Navigation Using an Auxiliary Particle Filter

In this research, a non-infrastructure-based and low-cost indoor navigation method is proposed through the integration of smartphone built-in microelectromechanical systems (MEMS) sensors and indoor map information using an auxiliary particle filter (APF). A cascade structure Kalman particle filter algorithm is designed to reduce the computational burden and improve the estimation speed of the ...

Robot Arm Performing Writing through Speech Recognition Using Dynamic Time Warping Algorithm

This paper aims to develop a writing robot by recognizing the speech signal from the user. The robot arm constructed mainly for the disabled people who can’t perform writing on their own. Here, dynamic time warping (DTW) algorithm is used to recognize the speech signal from the user. The action performed by the robot arm in the environment is done by reducing the redundancy which frequently fac...

Dynamic Time Warping Algorithm Review

Multivariate time series classification with parametric derivative dynamic time warping

Multivariate time series (MTS) data are widely used in a very broad range of fields, including medicine, finance, multimedia and engineering. In this paper a new approach for MTS classification, using a parametric derivative dynamic time warping distance, is proposed. Our approach combines two distances: the DTW distance between MTS and the DTW distance between derivatives of MTS. The new dista...