skip to main content


Title: Blind Source Separation for Surface Electromyograms Using a Bayesian Approach
This paper presents a blind source separation algorithm to identify binary and sparse sources from convolutive mixtures with linear and time-invariant finite impulse responses. Our approach combines Bayesian algorithms for detecting source activity with a linear minimum mean-square error estimator to identify all the time samples when each source is active. The algorithm was implemented on simulated electromyo-grams to identify neural commands. Our algorithm identified more than 96% of the sources on average with 16 or more measurement channels and SNR >= 14dB. For the detected sources, this algorithm correctly identified more than 94% of the samples on average. This performance was significantly better than that of a competing algorithm available in the literature.  more » « less
Award ID(s):
1901492
NSF-PAR ID:
10480784
Author(s) / Creator(s):
;
Publisher / Repository:
IEEE
Date Published:
Journal Name:
Proc. 30th European Signal Processing Conference
ISBN:
978-90-827970-9-1
Page Range / eLocation ID:
1956 to 1960
Subject(s) / Keyword(s):
Blind source separation Bayesian classification Linear minimum mean-square error estimator Sparsity-aware processing
Format(s):
Medium: X
Location:
Belgrade, Serbia
Sponsoring Org:
National Science Foundation
More Like this
  1. This paper explores an inverse approach to the problem of characterizing sediment sources' (“source” samples) age distributions based on samples from a particular depocenter (“sink” samples) using non-negative matrix factorization (NMF). It also outlines a method to determine the optimal number of sources to factorize from a set of sink samples (i.e., the optimum factorization rank). We demonstrate the power of this method by generating sink samples as random mixtures of known sources, factorizing them, and recovering the number of known sources, their age distributions, and the weighting functions used to generate the sink samples. Sensitivity testing indicates that similarity between factorized and known sources is positively correlated to 1) the number of sink samples, 2) the dissimilarity among sink samples, and 3) sink sample size. Specifically, the algorithm yields consistent, close similarity between factorized and known sources when the number of sink samples is more than ∼3 times the number of source samples, sink data sets are internally dissimilar (cross-correlation coefficient range >0.3, Kuiper V value range >0.35), and sink samples are well-characterized (>150–225 data points). However, similarity between known and factorized sources can be maintained while decreasing some of these variables if other variables are increased. Factorization of three empirical detrital zircon U–Pb data sets from the Book Cliffs, the Grand Canyon, and the Gulf of Mexico yields plausible source age distributions and weights. Factorization of the Book Cliffs data set yields five sources very similar to those recently independently proposed as the primary sources for Book Cliffs strata; confirming the utility of the NMF approach. The Grand Canyon data set exemplifies two general considerations when applying the NMF algorithm. First, although the NMF algorithm is able to identify source age distribution, additional geological details are required to discriminate between primary or recycled sources. Second, the NMF algorithm will identify the most basic elements of the mixed sink samples and so may subdivide sources that are themselves heterogeneous mixtures of more basic elements into those basic elements. Finally, application to a large Gulf of Mexico data set highlights the increased contribution from Appalachian sources during Cretaceous and Holocene time, potentially attributable to drainage reorganization. Although the algorithm reproduces known sources and yields reasonable sources for empirical data sets, inversions are inherently non-unique. Consequently, the results of NMF and their interpretations should be evaluated in light of independent geological evidence. The NMF algorithm is provided both as MATLAB code and a stand-alone graphical user interface for Windows and macOS (.exe and .app) along with all data sets discussed in this contribution. 
    more » « less
  2. ABSTRACT

    We present the identifications of a flux-limited sample of highly variable X-ray sources on long time-scales from the second catalogue of the XMM–Newton SLew survey (XMMSL2). The carefully constructed sample, comprising 265 sources (2.5 per cent) selected from the XMMSL2 clean catalogue, displayed X-ray variability of a factor of more than 10 in 0.2–2 keV compared to the ROSAT All Sky Survey. Of the sample sources, 94.3 per cent are identified. The identification procedure follows a series of cross-matches with astronomical data bases and multiwavelength catalogues to refine the source position and identify counterparts to the X-ray sources. Assignment of source type utilizes a combination of indicators including counterparts offset, parallax measurement, spectral colours, X-ray luminosity, and light-curve behaviour. We identified 40 per cent of the variables with stars, 10 per cent with accreting binaries, and at least 30.4 per cent with active galactic nuclei. The rest of the variables are identified as galaxies. It is found that the mean effective temperatures of the highly variable stars are lower than those of less variable stars. Our sample of highly variable AGN tend to have lower black hole masses, redshifts, and marginally lower soft X-ray luminosities compared to the less variable ones, while no difference was found in the Eddington ratio distributions. Five flaring events are tidal disruption events published previously. This study has significantly increased the number of variable sources in XMMSL2 with identifications and provides greater insight on the nature of many o f the sources, enabling further studies of highly variable X-ray sources.

     
    more » « less
  3. Abstract

    We present an automated method to identify high‐frequency geomagnetic disturbances in ground magnetometer data and classify the events by the source of the perturbations. We developed an algorithm to search for and identify changes in the surface magnetic field, dB/dt, with user‐specified amplitude and timescale. We used this algorithm to identify transient‐large‐amplitude (TLA) dB/dtevents that have timescale less than 60 s and amplitude >6 nT/s. Because these magnetic variations have similar amplitude and time characteristics to instrumental or man‐made noise, the algorithm identified a large number of noise‐type signatures as well as geophysical signatures. We manually classified these events by their sources (noise‐type or geophysical) and statistically characterized each type of event; the insights gained were used to more specifically define a TLA geophysical event and greatly reduce the number of noise‐type dB/dtidentified. Next, we implemented a support vector machine classification algorithm to classify the remaining events in order to further reduce the number of noise‐type dB/dtin the final data set. We examine the performance of our complete dB/dtsearch algorithm in widely used magnetometer databases and the effect of a common data processing technique on the results. The automated algorithm is a new technique to identify geomagnetic disturbances and instrumental or man‐made noise, enabling systematic identification and analysis of space weather related dB/dtevents and automated detection of magnetometer noise intervals in magnetic field databases.

     
    more » « less
  4. Abstract

    Urbanization negatively impacts water quality in streams by reducing stream‐groundwater interactions, which can reduce a stream's capacity to naturally attenuate nitrate. Meadowbrook Creek, a first order urban stream in Syracuse, New York, has an inverse urbanization gradient, with heavily urbanized headwaters that are disconnected from the floodplain and downstream reaches that have intact riparian floodplains and connection to riparian aquifers. This system allows assessment of how stream‐groundwater interactions in urban streams impact the net sources and sinks of nitrate at the reach scale. We used continuous (15‐min) streamflow measurements and weekly grab samples at three gauging stations positioned longitudinally along the creek to develop continuous nitrate load estimates at the inlet and outlet of two contrasting reaches. Nitrate load estimates were determined using a USGS linear regression model, RLOADEST, and differences between loads at the inlet and outlet of contrasting reaches were used to quantify nitrate sink and source behaviour year‐round. We observed a nitrate load of 1.4 × 104 kg NO3per water year, on average, at the outlet of the urbanized reach while the nitrate load at the outlet of the downstream, connected reach was 1.0 × 104 kg NO3per water year, on average. We found the more heavily urbanized, hydrologically‐disconnected reach was a net source of nitrate regardless of season. In contrast, stream‐groundwater exchange caused the hydrologically connected reach to be both a source and sink for nitrate, depending on time of year. Both reaches alter nitrate source and sink behaviour at various spatiotemporal scales. Groundwater connection in the downstream, connected reach reduces annual nitrate loads and provides more opportunities for sources and sinks of nitrate year‐round than the hydrologically disconnected stream reach. Mechanisms include groundwater discharge into the stream with variable nitrate concentrations, surface‐water groundwater interactions that foster denitrification, and stream load loss to surrounding near‐stream aquifers. This study emphasizes how loads are important in understanding how stream‐groundwater interactions impact reach scale nitrate export in urban streams.

     
    more » « less
  5. ABSTRACT Although the Brune source model describes earthquake moment release as a single pulse, it is widely used in studies of complex earthquakes with multiple episodes of high moment release (i.e., multiple subevents). In this study, we investigate how corner frequency estimates of earthquakes with multiple subevents are biased if they are based on the Brune source model. By assuming complex sources as a sum of multiple Brune sources, we analyze 1640 source time functions of Mw 5.5–8.0 earthquakes in the seismic source characteristic retrieved from deconvolving teleseismic body waves catalog to estimate the corner frequencies, onset times, and seismic moments of subevents. We identify more subevents for strike-slip earthquakes than dip-slip earthquakes, and the number of resolvable subevents increases with magnitude. We find that earthquake corner frequency correlates best with the corner frequency of the subevent with the highest moment release (i.e., the largest subsevent). This suggests that, when the Brune model is used, the estimated corner frequency and, therefore, the stress drop of a complex earthquake is determined primarily by the largest subevent rather than the total rupture area. Our results imply that, in addition to the simplified assumption of a radial rupture area with a constant rupture velocity, the stress variation of asperities, rather than the average stress change of the whole fault, contributes to the large variance of stress-drop estimates. 
    more » « less