... 1–14
DOI 10.1155/ASP/2006/35043
Supervised Self-Organizing Classification of Superresolution
ISAR Images: An Anechoic Chamber Experiment
Emanuel Radoi, Andr
´
e Quinquis, and Felix Totir
ENSIETA, E3I2 ... paper for the
supervised self-organizing classification of superresolution
ISAR images. The proposed approach is suitable for the clas-
sification of radar tar...
... the classification of time series data.
Actually Gaussian RBF kernel can be regarded as an
embedding of Euclidean distance in the form of Gaussian
function. Motivated by the effectiveness of ERP, ... achieves an
average classification rate of 91.74%, which is higher than
or comparable with those of other state -of- the-art pulse
waveform classification methods.
One potential...
... d
child1
and d
child2
are the Euclidian distances of
subbands nodes of mother node where as d
mother
is the dis-
tance of the mother node.
4. RESULTS
One thousand cracked and one thousand uncracked ... envelope of the im-
pact signal and all are used for classification. In the subband-
based algorithm [8], features were extracted from subband
signals and the 20 most relevant features...
... important
indication about the resorption mechanism and the role of
stromal cells in the structural change of scaffold. Canoni-
cal correlation analysis reveals as a valid tool for a system-
atic analysis ... P. Pels, L. De Lathauwer, P. Van Hecke, and S.
Van Huffel, “Tissue segmentation and classification of MRSI
data using canonical correlation analysis,” Magnetic Resonance
in Medicine...
... expressions of
the diagonal slice of second- , third- , and fourthorder cumu-
lant elements of a zero mean and stationary random vector z,
which is assumed to be one of the vectors f
− E{f}, h − E{h},
and ... total number of features,
m
1
and m
2
,andD
2
1
and D
2
2
are the means and variances vec-
tors of parameters vectors p
1,k
, k = 1, 2, , M
p
,andp
2,k
,
k
= 1, 2, , M
p
. p...
... understanding and
“translating” several types of power quality disturbances into
the perspective of signal processing. With visual inspection
of the waveform or the spectra of disturbances, the ... recognition of power quality disturbances,” IEEE
Transactions on Power Delivery, vol. 17, no. 2, pp. 609–616,
2002.
[12] S J. Huang, T M. Yang, and J T. Huang, “FPGA realization of
wave...
... combines techniques from [11]and
makes use of an eigenvalue analysis to give an indication
of the distance that an unknown sample vector is from the
feature space of each database. This indication ... large,
human oversight and control of low-level operations is not feasible. Coordination and self-organization of multiple autonomous
nodes is necessary to maintain connectivity...
... to handle, e.g., pas-
sivization and nominalization. This concerns the
canonical example of spill the beans, and many oth-
ers.
It follows that the units in the second group
should not, and probably ... distin-
guishing two groups of units: idiosyncratic from
the point of view of morphosyntax and idiosyn-
cratic from the point of view of semantics. Such
a division allows for efficie...
... in advance. Figure 3 shows the NMSE
R
contour set for two levels of sparsity (k/n = 0.15 and k/n =
0.25) as a function of the number of projections m and of
the quantization distortion of the ... audio stream and possibly affecting its
semantic content. Examples of this second kind of attacks
are the alteration of a piece of evidence in a criminal trial, or
the manipulation...
... contribution of feature selection to the variance of the deviation distri-
bution can be significant, contributing to over half of the variance in many of the cases studied. We consider linear-discriminant
analysis, ... covariance model. The squared biases are in 10
−4
unit, the same as deviation variances.
N Classifier
t-test SFS SFFS
Mean
2
(ΔE) Mean
2
(ΔE
b
) Mean
2
(ΔE) Mean
2
(ΔE
b...