17,443 research outputs found
Baseline correction for NMR spectroscopic metabolomics data analysis.
BackgroundWe propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of baseline distortion and constructs an optimal baseline curve to maximize it. The parameters are determined automatically by using LOWESS (locally weighted scatterplot smoothing) regression to estimate the noise variance.ResultsWe tested this method on 1D NMR spectra with different forms of baseline distortions, and demonstrated that it is effective for both regular 1D NMR spectra and metabolomics spectra with over-crowded peaks.ConclusionCompared with the automatic baseline correction function in XWINNMR 3.5, the penalized smoothing method provides more accurate baseline correction for high-signal density metabolomics spectra
Distributed Algorithms for Spectrum Allocation, Power Control, Routing, and Congestion Control in Wireless Networks
We develop distributed algorithms to allocate resources in multi-hop wireless
networks with the aim of minimizing total cost. In order to observe the
fundamental duplexing constraint that co-located transmitters and receivers
cannot operate simultaneously on the same frequency band, we first devise a
spectrum allocation scheme that divides the whole spectrum into multiple
sub-bands and activates conflict-free links on each sub-band. We show that the
minimum number of required sub-bands grows asymptotically at a logarithmic rate
with the chromatic number of network connectivity graph. A simple distributed
and asynchronous algorithm is developed to feasibly activate links on the
available sub-bands. Given a feasible spectrum allocation, we then design
node-based distributed algorithms for optimally controlling the transmission
powers on active links for each sub-band, jointly with traffic routes and user
input rates in response to channel states and traffic demands. We show that
under specified conditions, the algorithms asymptotically converge to the
optimal operating point.Comment: 14 pages, 5 figures, submitted to IEEE/ACM Transactions on Networkin
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