Robust Physiological Metrics From Sparsely Sampled Networks
نویسندگان
چکیده
منابع مشابه
Learning Regulatory Networks from Sparsely Sampled Time Series Expression Data
We present a probabilistic modeling approach to learning gene transcriptional regulation networks from time series gene expression data that is appropriate for the sparsely and irregularly sampled time series datasets currently available. We use a clustering algorithm based on statistical splines to estimate continuous probabilistic models for clusters of genes with similar time expression prof...
متن کاملTelescope alignment from sparsely sampled wavefront measurements over pupil subapertures.
We present a simple formalism that has proven useful in on-axis alignment of two-element telescopes when wavefront information is available from only a limited region (here two noncontiguous subapertures) of the pupil. Misalignments cause predictable full-aperture aberrations, which in turn cause predictable tip/tilt modes in the subapertures. For the most useful case in which secondary mirror ...
متن کاملRecovering the Precise Heart Rate from Sparsely Sampled Electrocardiograms
This work deals with a potential possibilities of improvement to the precision of time dependencies (e. g. heart rate) derived from a standard digital Holter record. The sampling frequency of a typical 24-hour ECG record is usually a compromise between signal quality and memory requirements. But even with a sampling interval of about 8 ms, is still possible to maintain the accuracy of 1...2 ms ...
متن کاملInferring Road Maps from Sparsely-Sampled GPS Traces
In this paper, we proposed a new segmentation-and-grouping framework for road map inference from sparsely-sampled GPS traces. First, we extended DBSCAN with the orientation constraint to partition the whole point set of traces to clusters representing road segments. Second, we proposed an adaptive k-means algorithm that the k value is determined by an angle threshold to reconstruct nearly strai...
متن کاملMicro-earthquake monitoring with sparsely-sampled data
Micro-seismicity can be used to monitor the migration of fluids during reservoir production and hydro-fracturing operations in brittle formations or for studies of naturally occurring earthquakes in fault zones. Micro-earthquake locations can be inferred using wave-equation imaging under the exploding reflector model, assuming densely sampled data and known velocity. Seismicity is usually monit...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Physiology
سال: 2021
ISSN: 1664-042X
DOI: 10.3389/fphys.2021.624097