783 research outputs found
Sparse Linear Models applied to Power Quality Disturbance Classification
Power quality (PQ) analysis describes the non-pure electric signals that are
usually present in electric power systems. The automatic recognition of PQ
disturbances can be seen as a pattern recognition problem, in which different
types of waveform distortion are differentiated based on their features.
Similar to other quasi-stationary signals, PQ disturbances can be decomposed
into time-frequency dependent components by using time-frequency or time-scale
transforms, also known as dictionaries. These dictionaries are used in the
feature extraction step in pattern recognition systems. Short-time Fourier,
Wavelets and Stockwell transforms are some of the most common dictionaries used
in the PQ community, aiming to achieve a better signal representation. To the
best of our knowledge, previous works about PQ disturbance classification have
been restricted to the use of one among several available dictionaries. Taking
advantage of the theory behind sparse linear models (SLM), we introduce a
sparse method for PQ representation, starting from overcomplete dictionaries.
In particular, we apply Group Lasso. We employ different types of
time-frequency (or time-scale) dictionaries to characterize the PQ
disturbances, and evaluate their performance under different pattern
recognition algorithms. We show that the SLM reduce the PQ classification
complexity promoting sparse basis selection, and improving the classification
accuracy
Shape theory via polar decomposition
This work proposes a new model in the context of statistical theory of shape,
based on the polar decomposition. The non isotropic noncentral elliptical shape
distributions via polar decomposition is derived in the context of zonal
polynomials, avoiding the invariant polynomials and the open problems for their
computation. The new polar shape distributions are easily computable and then
the inference procedure can be studied under exact densities. As an example of
the technique, a classical application in Biology is studied under three
models, the usual Gaussian and two non normal Kotz models; the best model is
selected by a modified BIC criterion, then a test for equality in polar shapes
is performed.Comment: 14 page
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