Abstract: By using the method of coincidence degree and constructing suitable Lyapunov functional, some sufficient conditions are established for the existence and global exponential stability of antiperiodic solutions for a kind of impulsive Cohen-Grossberg shunting inhibitory cellular neural networks (CGSICNNs) on time scales. An example is given to illustrate our results.
Abstract: Due to the liberalization of countless electricity markets, load forecasting has become crucial to all public utilities for which electricity is a strategic variable. With the goal of contributing to the forecasting process inside public utilities, this paper addresses the issue of applying the Holt-Winters exponential smoothing technique and the time series analysis for forecasting the hourly electricity load curve of the Italian railways. The results of the analysis confirm the accuracy of the two models and therefore the relevance of forecasting inside public utilities.
Abstract: In this paper, the potential use of an exponential
hidden Markov model to model a hidden pavement deterioration
process, i.e. one that is not directly measurable, is investigated. It is
assumed that the evolution of the physical condition, which is the
hidden process, and the evolution of the values of pavement distress
indicators, can be adequately described using discrete condition states
and modeled as a Markov processes. It is also assumed that condition
data can be collected by visual inspections over time and represented
continuously using an exponential distribution. The advantage of
using such a model in decision making process is illustrated through
an empirical study using real world data.
Abstract: The simulation of extrusion process is studied widely
in order to both increase products and improve quality, with broad
application in wire coating. The annular tube-tooling extrusion was
set up by a model that is termed as Navier-Stokes equation in
addition to a rheological model of differential form based on singlemode
exponential Phan-Thien/Tanner constitutive equation in a twodimensional
cylindrical coordinate system for predicting the
contraction point of the polymer melt beyond the die. Numerical
solutions are sought through semi-implicit Taylor-Galerkin pressurecorrection
finite element scheme. The investigation was focused on
incompressible creeping flow with long relaxation time in terms of
Weissenberg numbers up to 200. The isothermal case was considered
with surface tension effect on free surface in extrudate flow and no
slip at die wall. The Stream Line Upwind Petrov-Galerkin has been
proposed to stabilize solution. The structure of mesh after die exit
was adjusted following prediction of both top and bottom free
surfaces so as to keep the location of contraction point around one
unit length which is close to experimental results. The simulation of
extrusion process is studied widely in order to both increase products
and improve quality, with broad application in wire coating. The
annular tube-tooling extrusion was set up by a model that is termed
as Navier-Stokes equation in addition to a rheological model of
differential form based on single-mode exponential Phan-
Thien/Tanner constitutive equation in a two-dimensional cylindrical
coordinate system for predicting the contraction point of the polymer
melt beyond the die. Numerical solutions are sought through semiimplicit
Taylor-Galerkin pressure-correction finite element scheme.
The investigation was focused on incompressible creeping flow with
long relaxation time in terms of Weissenberg numbers up to 200. The
isothermal case was considered with surface tension effect on free
surface in extrudate flow and no slip at die wall. The Stream Line
Upwind Petrov-Galerkin has been proposed to stabilize solution. The
structure of mesh after die exit was adjusted following prediction of
both top and bottom free surfaces so as to keep the location of
contraction point around one unit length which is close to
experimental results.
Abstract: Speckled images arise when coherent microwave,
optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar
systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted
by speckle noise is complicated by the nature of the noise and is not
as straightforward as detection and estimation in additive noise. In
this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The
motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this
context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series
of Laguerre weighted exponential functions, resulting in a doubly
stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form.
It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an
exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.
Abstract: In this paper, the absorption and fluorescence
emission spectra of Yb:Y3Al5O12 (YAG)(25 at%) crystal as a disk
laser medium are measured at high temperature (300-450K). The
absorption and emission cross sections of Yb:YAG crystal are
determined using Reciprocity method. Temperature dependence of
941nm absorption cross section and 1031nm emission cross section
is extracted in the range of 300-450K. According to our experimental
results, an exponential temperature dependence between 300K and
450K is acquired for the 1031nm peak emission cross section and
also for 941nm peak absorption cross section of Yb:YAG crystal.
These results could be used for simulation and design of high power
highly doped Yb:YAG thin disk lasers.
Abstract: This paper investigates the problem of exponential stability for a class of uncertain discrete-time stochastic neural network with time-varying delays. By constructing a suitable Lyapunov-Krasovskii functional, combining the stochastic stability theory, the free-weighting matrix method, a delay-dependent exponential stability criteria is obtained in term of LMIs. Compared with some previous results, the new conditions obtain in this paper are less conservative. Finally, two numerical examples are exploited to show the usefulness of the results derived.
Abstract: In this paper, a class of generalized bi-directional associative memory (BAM) neural networks with mixed delays is investigated. On the basis of Lyapunov stability theory and contraction mapping theorem, some new sufficient conditions are established for the existence and uniqueness and globally exponential stability of equilibrium, which generalize and improve the previously known results. One example is given to show the feasibility and effectiveness of our results.
Abstract: In this paper, stabilization of an Active Magnetic Bearing (AMB) system with varying rotor speed using Sliding Mode Control (SMC) technique is considered. The gyroscopic effect inherited in the system is proportional to rotor speed in which this nonlinearity effect causes high system instability as the rotor speed increases. Also, transformation of the AMB dynamic model into a new class of uncertain system shows that this gyroscopic effect lies in the mismatched part of the system matrix. Moreover, the current gain parameter is allowed to be varied in a known bound as an uncertainty in the input matrix. SMC design method is proposed in which the sufficient condition that guarantees the global exponential stability of the reduced-order system is represented in Linear Matrix Inequality (LMI). Then, a new chattering-free control law is established such that the system states are driven to reach the switching surface and stay on it thereafter. The performance of the controller applied to the AMB model is demonstrated through simulation works under various system conditions.
Abstract: In this paper, a class of impulsive BAM fuzzy cellular neural networks with distributed delays and reaction-diffusion terms is formulated and investigated. By employing the delay differential inequality and inequality technique developed by Xu et al., some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with distributed delays and reaction-diffusion terms are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters, diffusion effect and impulsive disturbed intention. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.
Abstract: This paper presented a theoretical and numerical investigation of the Compact Antenna Test Range (CATR) equipped with Super Hybrid Modulated Segmented Exponential Serrations (SHMSES). The investigation was based on diffraction theory and, more specifically, the Fresnel diffraction formulation. The CATR provides uniform illumination within the Fresnel region to test antenna. Application of serrated edges has been shown to be a good method to control diffraction at the edges of the reflectors. However, in order to get some insight into the positive effect of serrated edges a less rigorous analysis technique known as Physical Optics (PO) may be used. Ripple free and enhanced quiet zone width are observed for specific values of width and height modulation factors per serrations. The performance of SHMSE serrated reflector is evaluated in order to observe the effects of edge diffraction on the test zone fields.
Abstract: In this paper, the robust exponential stability problem of uncertain discrete-time recurrent neural networks with timevarying delay is investigated. By constructing a new augmented Lyapunov-Krasovskii function, some new improved stability criteria are obtained in forms of linear matrix inequality (LMI). Compared with some recent results in literature, the conservatism of the new criteria is reduced notably. Two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.
Abstract: In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.
Abstract: This paper is concerned with exponential stability and stabilization of switched linear systems with interval time-varying delays. The time delay is any continuous function belonging to a given interval, in which the lower bound of delay is not restricted to zero. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton-s formula, a switching rule for the exponential stability and stabilization of switched linear systems with interval time-varying delays and new delay-dependent sufficient conditions for the exponential stability and stabilization of the systems are first established in terms of LMIs. Numerical examples are included to illustrate the effectiveness of the results.
Abstract: Due to new distributed database applications such as
huge deductive database systems, the search complexity is constantly
increasing and we need better algorithms to speedup traditional
relational database queries. An optimal dynamic programming
method for such high dimensional queries has the big disadvantage of
its exponential order and thus we are interested in semi-optimal but
faster approaches. In this work we present a multi-agent based
mechanism to meet this demand and also compare the result with
some commonly used query optimization algorithms.
Abstract: Computer based geostatistical methods can offer effective data analysis possibilities for agricultural areas by using
vectorial data and their objective informations. These methods will help to detect the spatial changes on different locations of the large
agricultural lands, which will lead to effective fertilization for optimal yield with reduced environmental pollution. In this study, topsoil (0-20 cm) and subsoil (20-40 cm) samples were taken from a
sugar beet field by 20 x 20 m grids. Plant samples were also collected
from the same plots. Some physical and chemical analyses for these
samples were made by routine methods. According to derived variation coefficients, topsoil organic matter (OM) distribution was more than subsoil OM distribution. The highest C.V. value of
17.79% was found for topsoil OM. The data were analyzed
comparatively according to kriging methods which are also used
widely in geostatistic. Several interpolation methods (Ordinary,Simple and Universal) and semivariogram models (Spherical,
Exponential and Gaussian) were tested in order to choose the suitable
methods. Average standard deviations of values estimated by simple
kriging interpolation method were less than average standard
deviations (topsoil OM ± 0.48, N ± 0.37, subsoil OM ± 0.18) of measured values. The most suitable interpolation method was simple
kriging method and exponantial semivariogram model for topsoil,
whereas the best optimal interpolation method was simple kriging
method and spherical semivariogram model for subsoil. The results
also showed that these computer based geostatistical methods should
be tested and calibrated for different experimental conditions and semivariogram models.
Abstract: Hazard rate estimation is one of the important topics
in forecasting earthquake occurrence. Forecasting earthquake
occurrence is a part of the statistical seismology where the main
subject is the point process. Generally, earthquake hazard rate is
estimated based on the point process likelihood equation called the
Hazard Rate Likelihood of Point Process (HRLPP). In this research,
we have developed estimation method, that is hazard rate single
decrement HRSD. This method was adapted from estimation method
in actuarial studies. Here, one individual associated with an
earthquake with inter event time is exponentially distributed. The
information of epicenter and time of earthquake occurrence are used
to estimate hazard rate. At the end, a case study of earthquake hazard
rate will be given. Furthermore, we compare the hazard rate between
HRLPP and HRSD method.
Abstract: This paper studies the pth moment exponential synchronization of a class of stochastic neural networks with mixed delays. Based on Lyapunov stability theory, by establishing a new integrodifferential inequality with mixed delays, several sufficient conditions have been derived to ensure the pth moment exponential stability for the error system. The criteria extend and improve some earlier results. One numerical example is presented to illustrate the validity of the main results.
Abstract: With the exponentially increasing demand for
wireless communications the capacity of current cellular systems will
soon become incapable of handling the growing traffic. Since radio
frequencies are diminishing natural resources, there seems to be a
fundamental barrier to further capacity increase. The solution can be
found in smart antenna systems.
Smart or adaptive antenna arrays consist of an array of antenna
elements with signal processing capability, that optimize the
radiation and reception of a desired signal, dynamically. Smart
antennas can place nulls in the direction of interferers via adaptive
updating of weights linked to each antenna element. They thus cancel
out most of the co-channel interference resulting in better quality of
reception and lower dropped calls. Smart antennas can also track the
user within a cell via direction of arrival algorithms. This implies that
they are more advantageous than other antenna systems. This paper
focuses on few issues about the smart antennas in mobile radio
networks.
Abstract: In this paper, we investigate dynamics of 2n almost periodic attractors for Cohen-Grossberg neural networks (CGNNs) with variable and distribute time delays. By imposing some new assumptions on activation functions and system parameters, we split invariant basin of CGNNs into 2n compact convex subsets. Then the existence of 2n almost periodic solutions lying in compact convex subsets is attained due to employment of the theory of exponential dichotomy and Schauder-s fixed point theorem. Meanwhile, we derive some new criteria for the networks to converge toward these 2n almost periodic solutions and exponential attracting domains are also given correspondingly.