45,436 research outputs found
Compressive Sensing of Analog Signals Using Discrete Prolate Spheroidal Sequences
Compressive sensing (CS) has recently emerged as a framework for efficiently
capturing signals that are sparse or compressible in an appropriate basis.
While often motivated as an alternative to Nyquist-rate sampling, there remains
a gap between the discrete, finite-dimensional CS framework and the problem of
acquiring a continuous-time signal. In this paper, we attempt to bridge this
gap by exploiting the Discrete Prolate Spheroidal Sequences (DPSS's), a
collection of functions that trace back to the seminal work by Slepian, Landau,
and Pollack on the effects of time-limiting and bandlimiting operations. DPSS's
form a highly efficient basis for sampled bandlimited functions; by modulating
and merging DPSS bases, we obtain a dictionary that offers high-quality sparse
approximations for most sampled multiband signals. This multiband modulated
DPSS dictionary can be readily incorporated into the CS framework. We provide
theoretical guarantees and practical insight into the use of this dictionary
for recovery of sampled multiband signals from compressive measurements
Development of a dc-ac power conditioner for wind generator by using neural network
This project present of development single phase DC-AC converter for wind
generator application. The mathematical model of the wind generator and Artificial
Neural Network control for DC-AC converter is derived. The controller is designed to
stabilize the output voltage of DC-AC converter. To verify the effectiveness of the
proposal controller, both simulation and experimental are developed. The simulation and
experimental result show that the amplitude of output voltage of the DC-AC converter
can be controlled
Frame Permutation Quantization
Frame permutation quantization (FPQ) is a new vector quantization technique
using finite frames. In FPQ, a vector is encoded using a permutation source
code to quantize its frame expansion. This means that the encoding is a partial
ordering of the frame expansion coefficients. Compared to ordinary permutation
source coding, FPQ produces a greater number of possible quantization rates and
a higher maximum rate. Various representations for the partitions induced by
FPQ are presented, and reconstruction algorithms based on linear programming,
quadratic programming, and recursive orthogonal projection are derived.
Implementations of the linear and quadratic programming algorithms for uniform
and Gaussian sources show performance improvements over entropy-constrained
scalar quantization for certain combinations of vector dimension and coding
rate. Monte Carlo evaluation of the recursive algorithm shows that mean-squared
error (MSE) decays as 1/M^4 for an M-element frame, which is consistent with
previous results on optimal decay of MSE. Reconstruction using the canonical
dual frame is also studied, and several results relate properties of the
analysis frame to whether linear reconstruction techniques provide consistent
reconstructions.Comment: 29 pages, 5 figures; detailed added to proof of Theorem 4.3 and a few
minor correction
Controlling symmetry and localization with an artificial gauge field in a disordered quantum system
Anderson localization, the absence of diffusion in disordered media, draws
its origins from the destructive interference between multiple scattering
paths. The localization properties of disordered systems are expected to be
dramatically sensitive to their symmetry characteristics. So far however, this
question has been little explored experimentally. Here, we investigate the
realization of an artificial gauge field in a synthetic (temporal) dimension of
a disordered, periodically-driven (Floquet) quantum system. Tuning the strength
of this gauge field allows us to control the time-reversal symmetry properties
of the system, which we probe through the experimental observation of three
symmetry-sensitive `smoking-gun' signatures of localization. The first two are
the coherent backscattering, marker of weak localization, and the coherent
forward scattering, genuine interferential signature of Anderson localization,
observed here for the first time. The third is the direct measurement of the
scaling function in two different symmetry classes, allowing to
demonstrate its universality and the one-parameter scaling hypothesis
Stochastic multi-channel lock-in detection
High-precision measurements benefit from lock-in detection of small signals.
Here we discuss the extension of lock-in detection to many channels, using
mutually orthogonal modulation waveforms, and show how the the choice of
waveforms affects the information content of the signal. We also consider how
well the detection scheme rejects noise, both random and correlated. We address
the particular difficulty of rejecting a background drift that makes a
reproducible offset in the output signal and we show how a systematic error can
be avoided by changing the waveforms between runs and averaging over many runs.
These advances made possible a recent measurement of the electron's electric
dipole moment.Comment: 11 pages, 3 figure
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