Sentence examples for based on dynamic time from inspiring English sources
Then, we classify such time series with a kernel based on dynamic time warping (DTW) and geodesic distances.
The above description summarizes related work in merging models within a cluster using Bayesian Factor, or using methods for Time Series Merging based on Dynamic Time warping.
To generate useful alarms in fault situations, an artificial immune system based on dynamic time warping (DTW) is used for fault detection and diagnosis.
The method treats each video activity as a temporal sequence of BoW features on a Riemannian manifold and classifies such time series with a kernel based on dynamic time warping (DTW) and geodesic distances.
In order to deal with the severe case of unlabeled data, a method is proposed based on dynamic time alignment of Gaussian mixture model clusters for matching actions in an unsupervised temporal segmentation.
Since different CGI + SS may contain a different number of GpG probes, we use a specific distance based on dynamic time warping to compare signatures of different lengths.
The lateral autopilot design is based on dynamic inversion and time scale separation principle.
Its robustness is evaluated relative to a PID control based on dynamic inversion; its rapid time response performance is compared with a conventional aircraft with fins only, to certify the effectiveness of the control moment allocator.
We show that these problems are NP-hard, and design algorithms based on dynamic programming (including pseudo-polynomial time optimal algorithms and fully polynomial time approximation schemes) to solve them.
The use of the Climate Surface method enables the application of holistic building optimization methods in the early design stages, where optimization methods based on dynamic simulation tools are too time consuming.
Finally, we consider the hybrid model of the models 2 and 3 to be the model 4. The Viterbi algorithm can compute the most probable state path of an HMM for a given sequence in O(m n) time based on dynamic programming, where m is the number of hidden states in the HMM and n is the sequence length.
