1,972 research outputs found
A polynomial rooting approach for synchronization in multipath channels using antenna arrays
The estimation of the delay of a known training signal received
by an antenna array in a multipath channel is addressed.
The effect of the co-channel interference is taken
into account by including a term with unknown spatial correlation.
The channel is modeled as an unstructured FIR
filter. The exact maximum likelihood (ML) solution for
this problem is derived, but it does not have a simple dependence
on the delay. An approximate estimator that is
asymptotically equivalent to the exact one is presented. Using
an appropriate reparameterization, it is shown that the
delay estimate is obtained by rooting a low-order polynomial,
which may be of interest in applications where fast
feedforward synchronization is needed.Peer ReviewedPostprint (published version
Photometric Mapping with ISOPHOT using the "P32" Astronomical Observation Template
The ``P32'' Astronomical Observation Template (AOT) provided a means to map
large areas of sky (up to 45 x 45 arcmin) in the far-infrared (FIR) at high
redundancy and with sampling close to the Nyquist limit using the ISOPHOT C100
(3 x 3) and C200 (2 x 2) detector arrays on board the Infrared Space
Observatory (ISO). However, the transient response behaviour of the Ga:Ge
detectors, if uncorrected, can lead to severe systematic photometric errors and
distortions of source morphology on maps. We describe the basic concepts of an
algorithm which can successfully correct for transient response artifacts in
P32 observations. Examples are given to demonstrate the photometric and imaging
performance of ISOPHOT P32 observations of point and extended sources corrected
using the algorithm. For extended sources we give the integrated flux densities
of the nearby galaxies NGC6946, M51 and M101 and an image of M101 at 100
micron.Comment: 15 pages, 16 figures, published in A&A 410, 107
The Stationary Phase Approximation, Time-Frequency Decomposition and Auditory Processing
The principle of stationary phase (PSP) is re-examined in the context of
linear time-frequency (TF) decomposition using Gaussian, gammatone and
gammachirp filters at uniform, logarithmic and cochlear spacings in frequency.
This necessitates consideration of the use the PSP on non-asymptotic integrals
and leads to the introduction of a test for phase rate dominance. Regions of
the TF plane that pass the test and don't contain stationary phase points
contribute little or nothing to the final output. Analysis values that lie in
these regions can thus be set to zero, i.e. sparsity. In regions of the TF
plane that fail the test or are in the vicinity of stationary phase points,
synthesis is performed in the usual way. A new interpretation of the location
parameters associated with the synthesis filters leads to: (i) a new method for
locating stationary phase points in the TF plane; (ii) a test for phase rate
dominance in that plane. Together this is a TF stationary phase approximation
(TFSFA) for both analysis and synthesis. The stationary phase regions of
several elementary signals are identified theoretically and examples of
reconstruction given. An analysis of the TF phase rate characteristics for the
case of two simultaneous tones predicts and quantifies a form of simultaneous
masking similar to that which characterizes the auditory system.Comment: Submitted to IEEE Trans Signal Processing 14th Aug 201
Phase correction for Learning Feedforward Control
Intelligent mechatronics makes it possible to compensate for effects that are difficult to compensate for by construction or by linear control, by including some intelligence into the system. The compensation of state dependent effects, e.g. friction, cogging and mass deviation, can be realised by learning feedforward control. This method identifies these disturbing effects as function of their states and compensates for these, before they introduce an error. Because the effects are learnt as function of their states, this method can be used for non-repetitive motions. The learning of state dependent effects relies on the update signal that is used. In previous work, the feedback control signal was used as an error measure between the approximation and the true state dependent effect. If the effects introduce a signal that contains frequencies near the bandwidth, the phase shift between this signal and the feedback signal might seriously degenerate the performance of the approximation. The use of phase correction overcomes this problem. This is validated by a set of simulations and experiments that show the necessity of the phase corrected scheme
Iterative learning control experimental results in twin-rotor device
This paper presents the results of applying the Iterative Learning Control algorithms to a Twin-Rotor Multiple-Input Multiple-Output System (TRMS) in order to achieve high performance in repetitive tracking of trajectories. The plant, which is similar to a prototype of helicopter, is characterized by its highly nonlinear and cross-coupled dynamics. In the first phase, the system is modelled using the Lagrangian approach and combining theoretical and experimental results. Thereafter, a hierarchical control architecture which combines a baseline feedback controller with an Iterative Learning Control algorithm is developed. Finally, the responses of the real device and a complete analysis of the learning behaviour are exposed.Postprint (published version
Subband Adaptive Modeling of Digital Hearing Aids
In this thesis, the application of a subband adaptive model to characterize compression behaviour of five digital hearing aids is investigated. Using a signal-to-error ratio metric, modeling performance is determined by varying the number of analysis bands in the subband structure as well as consideration of three adaptive algorithms. The normalized least mean-squares (NLMS), the affine projection algorithm (APA), and the recursive least-squares (RLS) algorithms are employed using a range of parameters to determine the impact on modeling performance. Using the subband adaptive model to estimate the time-varying frequency response of each hearing aid allows the Perceptual Evaluation of Speech Quality (PESQ) mean-opinion score (MOS) to be computed. The PESQ MOS facilitates an estimation of a subjective assessment of speech quality using an objective score. Initial results suggest the PESQ MOS score is able to differentiate speech processed by hearing aids allowing them to be ranked accordingly. Further work is required to obtain subjective assessments of the processed speech signals and determine if possible correlations exist
Telling cause from effect in deterministic linear dynamical systems
Inferring a cause from its effect using observed time series data is a major
challenge in natural and social sciences. Assuming the effect is generated by
the cause trough a linear system, we propose a new approach based on the
hypothesis that nature chooses the "cause" and the "mechanism that generates
the effect from the cause" independent of each other. We therefore postulate
that the power spectrum of the time series being the cause is uncorrelated with
the square of the transfer function of the linear filter generating the effect.
While most causal discovery methods for time series mainly rely on the noise,
our method relies on asymmetries of the power spectral density properties that
can be exploited even in the context of deterministic systems. We describe
mathematical assumptions in a deterministic model under which the causal
direction is identifiable with this approach. We also discuss the method's
performance under the additive noise model and its relationship to Granger
causality. Experiments show encouraging results on synthetic as well as
real-world data. Overall, this suggests that the postulate of Independence of
Cause and Mechanism is a promising principle for causal inference on empirical
time series.Comment: This article is under review for a peer-reviewed conferenc
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