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for a substantial time in advance. I apply the
tunable system identification for eliminating the
zeros but not the overflows. Once that convolution
integrals have been set off the parameters
I move the time steps forward and backward for
T= - 1 and T = -2 because the past time steps
are necessary for identifying the possible source
of collapses. When the parameters are tested to
be positive all them stay for a next evaluation
with different values. This operation is repeated
once more time and the results are seen in the
figure 2 when the collapse situations are under
control with only one collapse remains.
Fig. 2.- Recovering of tunable system by
reducing the instabilities which appear as
consequence of the choice parameters set
constants for next and previous time steps.
In figure 2 also one sees the presence of the
collapsing over the 14 th time step. It tells that
a new evaluation should be done. It is done
and the figure 3 which indicates the absence
of collapses to zero but still remains the values
which provides overflow to the system. Finally
en figure 3 one sees the absence of overflows
which means besides the termination of attacks
aftermaths. However there are some small fallings
but the systems is recovered sudden and
fast within a range of 1/10 time step. It has
an explanation: the tunable system is identified
just for the former parameters but the initial
shooting set parameters has to be changed
from a metric 0000001 to one 1100111. It is
because the first time steps are recorded with
errors since the 12 th up to the 14 th time step.
Two things: every system is sometimes composed
of real parameters and some time they
are depending on the complex part when the
transfer functions have zeros in their denominator.
It is not mandatory for tunable system identification,
because in this method we evaluate
directly by using the metric for each time step.
Second, the absence of attacks to some system
does not means that they should be build
without any strategy for stopping it for previous
evaluation of the convolution integral. For the
most general representation, system should
bring a protection mechanism to be tunable not
CIENCIA, CULTURA Y TECNOLOGÍA - UNIVERSIDAD TECNOLÓGICA DEL PERÚ
only time but also in parameters metric. Once
the metric is given for a few time steps the job
of any tunable system identification will be that
of predicting the future from those given at past
without any knowledge to priori. It represents
a firm advantage for trying identifying systems
which normally are not under control after successive
collapses and which would not have any
chance to be restored [3]. In future I will do
a similar study but with the simulation of time
step history for clarifying the hypothesis of tunable
system identification.
Fig. 3.- Full recovering of tunable system
without any zero but still the overflows are
not negligible. Tunable system identification is
therefore successfully applied.
Acknowledgments
I express my sincere thanks to Eng. Pamela
Calipuy, Eng. Alert Mendoza by their enormous
support in various aspects of my work at the
FIEM-UTP.
References
[1] Tunable microwave and millimeter-wave
band-pass filters Uher, J.; Hoefer, W.J.R.
Microwave Theory and Techniques, IEEE Transactions
on Volume 39, Issue: 4
Digital Object Identifier: 10.1109/22.76427
Publication Year: 1991 , Page(s): 643 – 653.
[2] MEMS-Based Tunable LC Bandstop Filter
With an Ultra-Wide Continuous Tuning Range
Hyung Suk Lee; Dong-Hoon Choi; Jun-Bo Yoon
Microwave and Wireless Components Letters,
IEEE Volume 19, Issue: 11
Digital-Object-Identifier:10.1109/LMWC.2009.
203210 Publication Year: 2009 , Page(s): 710
– 712.
[3] Synthesis of tunable optical waveguide filters
using digital signal processing technique
Nam Quoc-Ngo;Binh-L.N, Lightwave Technology,
Journal of Volume: 24 , Issue: 9
DigitalObjectIdentifier:10.1109/
JLT.2006.880160
Publication Year: 2006 , Page(s): 3520 – 3531.
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