646 research outputs found
Improved Energy Detector for Wideband Spectrum Sensing in Cognitive Radio Networks
In this paper, an improved energy detector for a wideband spectrum sensing is proposed. For a better detection of the spectrum holes the overall band is divided into equal non-overlapping sub-bands. The main objective is to determine the detection thresholds for each of these subbands jointly. By defining the problem as an optimization problem, we aim to find the maximum aggregated opportunistic throughput of cognitive radio networks. Introducing practical constraints to this optimization problem will change the problem into a convex and solvable one. The results of this paper show that the proposed improved energy detector will increase the aggregated throughput considerably
Antilocalization in Coulomb Blockade
We study the effect of spin-orbit scattering on the statistics of the
conductance of a quantum dot for Coulomb blockade peaks and valleys. We find
the distribution function of the peak heights for strong spin-orbit scattering
in the presence and absence of time reversal symmetry. We find that the
application of a magnetic field suppresses the average peak height, similar to
the antilocalizaion in the bulk systems. For the valleys, we consider the
elastic cotunneling contribution to the conductance and calculate its moments
at the crossover between ensembles of various symmetries.Comment: 4 pages, 2 figure
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Sniff Invariant Odor Coding.
Sampling regulates stimulus intensity and temporal dynamics at the sense organ. Despite variations in sampling behavior, animals must make veridical perceptual judgments about external stimuli. In olfaction, odor sampling varies with respiration, which influences neural responses at the olfactory periphery. Nevertheless, rats were able to perform fine odor intensity judgments despite variations in sniff kinetics. To identify the features of neural activity supporting stable intensity perception, in awake mice we measured responses of mitral/tufted (MT) cells to different odors and concentrations across a range of sniff frequencies. Amplitude and latency of the MT cells' responses vary with sniff duration. A fluid dynamics (FD) model based on odor concentration kinetics in the intranasal cavity can account for this variability. Eliminating sniff waveform dependence of MT cell responses using the FD model allows for significantly better decoding of concentration. This suggests potential schemes for sniff waveform invariant odor concentration coding
Acoustic phonon scattering in a low density, high mobility AlGaN/GaN field effect transistor
We report on the temperature dependence of the mobility, , of the
two-dimensional electron gas in a variable density AlGaN/GaN field effect
transistor, with carrier densities ranging from 0.4 cm to
3.0 cm and a peak mobility of 80,000 cm/Vs. Between
20 K and 50 K we observe a linear dependence T
indicating that acoustic phonon scattering dominates the temperature dependence
of the mobility, with being a monotonically increasing function of
decreasing 2D electron density. This behavior is contrary to predictions of
scattering in a degenerate electron gas, but consistent with calculations which
account for thermal broadening and the temperature dependence of the electron
screening. Our data imply a deformation potential D = 12-15 eV.Comment: 3 pages, 2 figures, RevTeX. Submitted to Appl Phys Let
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Heading direction with respect to a reference point modulates place-cell activity.
The tuning of neurons in area CA1 of the hippocampus emerges through a combination of non-spatial input from different sensory modalities and spatial information about the animal's position and heading direction relative to the spatial enclosure being navigated. The positional modulation of CA1 neuronal responses has been widely studied (e.g. place tuning), but less is known about the modulation of these neurons by heading direction. Here, utilizing electrophysiological recordings from CA1 pyramidal cells in freely moving mice, we report that a majority of neural responses are modulated by the heading-direction of the animal relative to a point within or outside their enclosure that we call a reference point. The finding of heading-direction modulation relative to reference points identifies a novel representation encoded in the neuronal responses of the dorsal hippocampus
Negative Echo in the Density Evolution of Ultracold Fermionic Gases
We predict a nonequilibrium critical phenomenon in the space-time density
evolution of a fermionic gas above the temperature of transition into the
superfluid phase. On the BCS side of the BEC-BCS crossover, the evolution of a
localized density disturbance exhibits a negative echo at the point of the
initial inhomogeneity. Approaching the BEC side, this effect competes with the
slow spreading of the density of bosonic molecules. However, even here the echo
dominates for large enough times. This effect may be used as an experimental
tool to locate the position of the transition.Comment: 4 pages, 2 figure
Sampling constrained probability distributions using Spherical Augmentation
Statistical models with constrained probability distributions are abundant in
machine learning. Some examples include regression models with norm constraints
(e.g., Lasso), probit, many copula models, and latent Dirichlet allocation
(LDA). Bayesian inference involving probability distributions confined to
constrained domains could be quite challenging for commonly used sampling
algorithms. In this paper, we propose a novel augmentation technique that
handles a wide range of constraints by mapping the constrained domain to a
sphere in the augmented space. By moving freely on the surface of this sphere,
sampling algorithms handle constraints implicitly and generate proposals that
remain within boundaries when mapped back to the original space. Our proposed
method, called {Spherical Augmentation}, provides a mathematically natural and
computationally efficient framework for sampling from constrained probability
distributions. We show the advantages of our method over state-of-the-art
sampling algorithms, such as exact Hamiltonian Monte Carlo, using several
examples including truncated Gaussian distributions, Bayesian Lasso, Bayesian
bridge regression, reconstruction of quantized stationary Gaussian process, and
LDA for topic modeling.Comment: 41 pages, 13 figure
Current tidal power technologies and their suitability for applications in coastal and marine areas
A considerable body of research is currently being performed to quantify available tidal energy resources and to develop efficient devices with which to harness them. This work is naturally focussed on maximising power generation from the most promising sites, and a review of the literature suggests that the potential for smaller scale, local tidal power generation from shallow near-shore sites has not yet been investigated. If such generation is feasible, it could have the potential to provide sustainable electricity for nearby coastal homes and communities as part of a distributed generation strategy, and would benefit from easier installation and maintenance, lower cabling and infrastructure requirements and reduced capital costs when compared with larger scale projects. This article reviews tidal barrages and lagoons, tidal turbines, oscillating hydrofoils and tidal kites to assess their suitability for small-scale electricity generation in shallow waters. This is achieved by discussing the power density, scalability, durability, maintainability, economic potential and environmental impacts of each concept. The performance of each technology in each criterion is scored against axial-flow turbines, allowing for them to be ranked according to their overall suitability. The review suggests that tidal kites and range devices are not suitable for small-scale shallow water applications due to depth and size requirements respectively. Cross-flow turbines appear to be the most suitable technology, as they have high power densities and a maximum size that is not constrained by water depth
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