13,387 research outputs found
General analytical solutions for DC/AC circuit-network analysis
All authors thank the Scottish University Physics Alliance (SUPA) support. NR also acknowledges de support of PEDECIBA, Uruguay. MSB acknowledges the support of EPSRC grant Ref. EP/I032606/1. Open access via Springer Compact Agreement.Peer reviewedPublisher PD
Spatio-temporal wavelet regularization for parallel MRI reconstruction: application to functional MRI
Parallel MRI is a fast imaging technique that enables the acquisition of
highly resolved images in space or/and in time. The performance of parallel
imaging strongly depends on the reconstruction algorithm, which can proceed
either in the original k-space (GRAPPA, SMASH) or in the image domain
(SENSE-like methods). To improve the performance of the widely used SENSE
algorithm, 2D- or slice-specific regularization in the wavelet domain has been
deeply investigated. In this paper, we extend this approach using 3D-wavelet
representations in order to handle all slices together and address
reconstruction artifacts which propagate across adjacent slices. The gain
induced by such extension (3D-Unconstrained Wavelet Regularized -SENSE:
3D-UWR-SENSE) is validated on anatomical image reconstruction where no temporal
acquisition is considered. Another important extension accounts for temporal
correlations that exist between successive scans in functional MRI (fMRI). In
addition to the case of 2D+t acquisition schemes addressed by some other
methods like kt-FOCUSS, our approach allows us to deal with 3D+t acquisition
schemes which are widely used in neuroimaging. The resulting 3D-UWR-SENSE and
4D-UWR-SENSE reconstruction schemes are fully unsupervised in the sense that
all regularization parameters are estimated in the maximum likelihood sense on
a reference scan. The gain induced by such extensions is illustrated on both
anatomical and functional image reconstruction, and also measured in terms of
statistical sensitivity for the 4D-UWR-SENSE approach during a fast
event-related fMRI protocol. Our 4D-UWR-SENSE algorithm outperforms the SENSE
reconstruction at the subject and group levels (15 subjects) for different
contrasts of interest (eg, motor or computation tasks) and using different
parallel acceleration factors (R=2 and R=4) on 2x2x3mm3 EPI images.Comment: arXiv admin note: substantial text overlap with arXiv:1103.353
Stored Electromagnetic Energy and Antenna Q
Decomposition of the electromagnetic energy into its stored and radiated
parts is instrumental in the evaluation of antenna Q and the corresponding
fundamental limitations on antennas. This decomposition is not unique and there
are several proposals in the literature. Here, it is shown that stored energy
defined from the difference between the energy density and the far field energy
equals the new energy expressions proposed by Vandenbosch for many cases. This
also explains the observed cases with negative stored energy and suggests a
possible remedy to them. The results are compared with the classical explicit
expressions for spherical regions where the results only differ by ka that is
interpreted as the far-field energy in the interior of the sphere. Numerical
results of the Q-factors for dipole, loop, and inverted L-antennas are also
compared with estimates from circuit models and differentiation of the
impedance. The results indicate that the stored energy in the field agrees with
the stored energy in the Brune synthesized circuit models whereas the
differentiated impedance gives a lower value for some cases. The corresponding
results for the bandwidth suggest that the inverse proportionality between
bandwidth and Q depends on the relative bandwidth or equivalent the threshold
of the reflection coefficient. The Q from the differentiated impedance and
stored energy are most useful for relative narrow and wide bandwidths,
respectively
Beamforming for Magnetic Induction based Wireless Power Transfer Systems with Multiple Receivers
Magnetic induction (MI) based communication and power transfer systems have
gained an increased attention in the recent years. Typical applications for
these systems lie in the area of wireless charging, near-field communication,
and wireless sensor networks. For an optimal system performance, the power
efficiency needs to be maximized. Typically, this optimization refers to the
impedance matching and tracking of the split-frequencies. However, an important
role of magnitude and phase of the input signal has been mostly overlooked.
Especially for the wireless power transfer systems with multiple transmitter
coils, the optimization of the transmit signals can dramatically improve the
power efficiency. In this work, we propose an iterative algorithm for the
optimization of the transmit signals for a transmitter with three orthogonal
coils and multiple single coil receivers. The proposed scheme significantly
outperforms the traditional baseline algorithms in terms of power efficiency.Comment: This paper has been accepted for presentation at IEEE GLOBECOM 2015.
It has 7 pages and 5 figure
Subanesthetic ketamine treatment promotes abnormal interactions between neural subsystems and alters the properties of functional brain networks
Acute treatment with subanesthetic ketamine, a non-competitive N-methyl-D-aspartic acid (NMDA) receptor antagonist, is widely utilized as a translational model for schizophrenia. However, how acute NMDA receptor blockade impacts on brain functioning at a systems level, to elicit translationally relevant symptomatology and behavioral deficits, has not yet been determined. Here, for the first time, we apply established and recently validated topological measures from network science to brain imaging data gained from ketamine-treated mice to elucidate how acute NMDA receptor blockade impacts on the properties of functional brain networks. We show that the effects of acute ketamine treatment on the global properties of these networks are divergent from those widely reported in schizophrenia. Where acute NMDA receptor blockade promotes hyperconnectivity in functional brain networks, pronounced dysconnectivity is found in schizophrenia. We also show that acute ketamine treatment increases the connectivity and importance of prefrontal and thalamic brain regions in brain networks, a finding also divergent to alterations seen in schizophrenia. In addition, we characterize how ketamine impacts on bipartite functional interactions between neural subsystems. A key feature includes the enhancement of prefrontal cortex (PFC)-neuromodulatory subsystem connectivity in ketamine-treated animals, a finding consistent with the known effects of ketamine on PFC neurotransmitter levels. Overall, our data suggest that, at a systems level, acute ketamine-induced alterations in brain network connectivity do not parallel those seen in chronic schizophrenia. Hence, the mechanisms through which acute ketamine treatment induces translationally relevant symptomatology may differ from those in chronic schizophrenia. Future effort should therefore be dedicated to resolve the conflicting observations between this putative translational model and schizophrenia
Learning, Categorization, Rule Formation, and Prediction by Fuzzy Neural Networks
National Science Foundation (IRI 94-01659); Office of Naval Research (N00014-91-J-4100, N00014-92-J-4015) Air Force Office of Scientific Research (90-0083, N00014-92-J-4015
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