Abstract: In this paper, the least-squares design of variable fractional-delay (VFD) finite impulse response (FIR) digital differentiators is proposed. The used transfer function is formulated so that Farrow structure can be applied to realize the designed system. Also, the symmetric characteristics of filter coefficients are derived, which leads to the complexity reduction by saving almost a half of the number of coefficients. Moreover, all the elements of related vectors or matrices for the optimal process can be represented in closed forms, which make the design easier. Design example is also presented to illustrate the effectiveness of the proposed method.
Abstract: This paper presents a new fingerprint coding technique
based on contourlet transform and multistage vector quantization.
Wavelets have shown their ability in representing natural images that
contain smooth areas separated with edges. However, wavelets
cannot efficiently take advantage of the fact that the edges usually
found in fingerprints are smooth curves. This issue is addressed by
directional transforms, known as contourlets, which have the
property of preserving edges. The contourlet transform is a new
extension to the wavelet transform in two dimensions using
nonseparable and directional filter banks. The computation and
storage requirements are the major difficulty in implementing a
vector quantizer. In the full-search algorithm, the computation and
storage complexity is an exponential function of the number of bits
used in quantizing each frame of spectral information. The storage
requirement in multistage vector quantization is less when compared
to full search vector quantization. The coefficients of contourlet
transform are quantized by multistage vector quantization. The
quantized coefficients are encoded by Huffman coding. The results
obtained are tabulated and compared with the existing wavelet based
ones.
Abstract: This paper presents a new algorithm for the channel estimation of the OFDM system based on a pilot signal for the new generation of high data rate communication systems. In orthogonal frequency division multiplexing (OFDM) systems over fast-varying fading channels, channel estimation and tracking is generally carried out by transmitting known pilot symbols in given positions of the frequency-time grid. In this paper, we propose to derive an improved algorithm based on the calculation of the mean and the variance of the adjacent pilot signals for a specific distribution of the pilot signals in the OFDM frequency-time grid then calculating of the entire unknown channel coefficients from the equation of the mean and the variance. Simulation results shows that the performance of the OFDM system increase as the length of the channel increase where the accuracy of the estimated channel will be increased using this low complexity algorithm, also the number of the pilot signal needed to be inserted in the OFDM signal will be reduced which lead to increase in the throughput of the signal over the OFDM system in compared with other type of the distribution such as Comb type and Block type channel estimation.
Abstract: Maize and Indian mustard are significant crops in
semi-arid climate zones of India. Improved water management
requires precise scheduling of irrigation, which in turn requires an
accurate computation of daily crop evapotranspiration (ETc). Daily
crop evapotranspiration comes as a product of reference
evapotranspiration (ET0) and the growth stage specific crop
coefficients modified for daily variation. The first objective of
present study is to develop crop coefficients Kc for Maize and Indian
mustard. The estimated values of Kc for maize at the four crop
growth stages (initial, development, mid-season, and late season) are
0.55, 1.08, 1.25, and 0.75, respectively, and for Indian mustard the Kc
values at the four growth stages are 0.3, 0.6, 1.12, and 0.35,
respectively. The second objective of the study is to compute daily
crop evapotranspiration from ET0 and crop coefficients. Average
daily ETc of maize varied from about 2.5 mm/d in the early growing
period to > 6.5 mm/d at mid season. The peak ETc of maize is 8.3
mm/d and it occurred 64 days after sowing at the reproductive growth
stage when leaf area index was 4.54. In the case of Indian mustard,
average ETc is 1 mm/d at the initial stage, >1.8 mm/d at mid season
and achieves a peak value of 2.12 mm/d on 56 days after sowing.
Improved schedules of irrigation have been simulated based on daily
crop evapo-transpiration and field measured data. Simulation shows a
close match between modeled and field moisture status prevalent
during crop season.
Abstract: The approach proposed here is oriented in the direction of fuzzy system for the analysis and the synthesis of intelligent climate controllers, the simulation of the internal climate of the greenhouse is achieved by a linear model whose coefficients are obtained by identification. The use of fuzzy logic controllers for the regulation of climate variables represents a powerful way to minimize the energy cost. Strategies of reduction and optimization are adopted to facilitate the tuning and to reduce the complexity of the controller.
Abstract: In this paper a novel scheme for watermarking digital
audio during its compression to MPEG-1 Layer III format is
proposed. For this purpose we slightly modify some of the selected
MDCT coefficients, which are used during MPEG audio
compression procedure. Due to the possibility of modifying different
MDCT coefficients, there will be different choices for embedding the
watermark into audio data, considering robustness and transparency
factors. Our proposed method uses a genetic algorithm to select the
best coefficients to embed the watermark. This genetic selection is
done according to the parameters that are extracted from the
perceptual content of the audio to optimize the robustness and
transparency of the watermark. On the other hand the watermark
security is increased due to the random nature of the genetic
selection. The information of the selected MDCT coefficients that
carry the watermark bits, are saves in a database for future extraction
of the watermark. The proposed method is suitable for online MP3
stores to pursue illegal copies of musical artworks. Experimental
results show that the detection ratio of the watermarks at the bitrate
of 128kbps remains above 90% while the inaudibility of the
watermark is preserved.
Abstract: In this paper, a new encoding algorithm of spectral envelope based on NLMS in G.729.1 for VoIP is proposed. In the TDAC part of G.729.1, the spectral envelope and MDCT coefficients extracted in the weighted CELP coding error (lower-band) and the higher-band input signal are encoded. In order to reduce allocation bits for spectral envelope coding, a new quantization algorithm based on NLMS is proposed. Also, reduced bits are used to enhance sound quality. The performance of the proposed algorithm is evaluated by sound quality and bit reduction rates in clean and frame loss conditions.
Abstract: Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually the effects of blurred edges and jagged artifacts in the image to some extent. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to sharpen edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (“jaggies") along the tangent directions. In order to preserve image features such as edges, corners and textures, the nonlinear diffusion coefficients are locally adjusted according to the directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Abstract: In this paper we present an autoregressive model with
neural networks modeling and standard error backpropagation
algorithm training optimization in order to predict the gross domestic
product (GDP) growth rate of four countries. Specifically we propose
a kind of weighted regression, which can be used for econometric
purposes, where the initial inputs are multiplied by the neural
networks final optimum weights from input-hidden layer after the
training process. The forecasts are compared with those of the
ordinary autoregressive model and we conclude that the proposed
regression-s forecasting results outperform significant those of
autoregressive model in the out-of-sample period. The idea behind
this approach is to propose a parametric regression with weighted
variables in order to test for the statistical significance and the
magnitude of the estimated autoregressive coefficients and
simultaneously to estimate the forecasts.
Abstract: In this paper we consider a nonlinear feedback control
called augmented automatic choosing control (AACC) using the
gradient optimization automatic choosing functions for nonlinear
systems. Constant terms which arise from sectionwise linearization
of a given nonlinear system are treated as coefficients of a stable
zero dynamics. Parameters included in the control are suboptimally
selected by expanding a stable region in the sense of Lyapunov
with the aid of the genetic algorithm. This approach is applied to
a field excitation control problem of power system to demonstrate
the splendidness of the AACC. Simulation results show that the new
controller can improve performance remarkably well.
Abstract: We seek exact solutions of the coupled Klein-Gordon-Schrödinger equation with variable coefficients with the aid of Lie classical approach. By using the Lie classical method, we are able to derive symmetries that are used for reducing the coupled system of partial differential equations into ordinary differential equations. From reduced differential equations we have derived some new exact solutions of coupled Klein-Gordon-Schrödinger equations involving some special functions such as Airy wave functions, Bessel functions, Mathieu functions etc.
Abstract: In this work a new method for low complexity
image coding is presented, that permits different settings and great
scalability in the generation of the final bit stream. This coding
presents a continuous-tone still image compression system that
groups loss and lossless compression making use of finite arithmetic
reversible transforms. Both transformation in the space of color and
wavelet transformation are reversible. The transformed coefficients
are coded by means of a coding system in depending on a
subdivision into smaller components (CFDS) similar to the bit
importance codification. The subcomponents so obtained are
reordered by means of a highly configure alignment system
depending on the application that makes possible the re-configure of
the elements of the image and obtaining different importance levels
from which the bit stream will be generated. The subcomponents of
each importance level are coded using a variable length entropy
coding system (VBLm) that permits the generation of an embedded
bit stream. This bit stream supposes itself a bit stream that codes a
compressed still image. However, the use of a packing system on the
bit stream after the VBLm allows the realization of a final highly
scalable bit stream from a basic image level and one or several
improvement levels.
Abstract: Smoothing or filtering of data is first preprocessing step
for noise suppression in many applications involving data analysis.
Moving average is the most popular method of smoothing the data,
generalization of this led to the development of Savitzky-Golay filter.
Many window smoothing methods were developed by convolving
the data with different window functions for different applications;
most widely used window functions are Gaussian or Kaiser. Function
approximation of the data by polynomial regression or Fourier
expansion or wavelet expansion also gives a smoothed data. Wavelets
also smooth the data to great extent by thresholding the wavelet
coefficients. Almost all smoothing methods destroys the peaks and
flatten them when the support of the window is increased. In certain
applications it is desirable to retain peaks while smoothing the data
as much as possible. In this paper we present a methodology called
as peak-wise smoothing that will smooth the data to any desired level
without losing the major peak features.
Abstract: A multicriteria linear programming problem with integer variables and parameterized optimality principle "from lexicographic to Slater" is considered. A situation in which initial coefficients of penalty cost functions are not fixed but may be potentially a subject to variations is studied. For any efficient solution, appropriate measures of the quality are introduced which incorporate information about variations of penalty cost function coefficients. These measures correspond to the so-called stability and accuracy functions defined earlier for efficient solutions of a generic multicriteria combinatorial optimization problem with Pareto and lexicographic optimality principles. Various properties of such functions are studied and maximum norms of perturbations for which an efficient solution preserves the property of being efficient are calculated.
Abstract: Fischer-Tropsch synthesis is one of the most
important catalytic reactions that convert the synthetic gas to light
and heavy hydrocarbons. One of the main issues is selecting the type
of reactor. The slurry bubble reactor is suitable choice for Fischer-
Tropsch synthesis because of its good qualification to transfer heat
and mass, high durability of catalyst, low cost maintenance and
repair. The more common catalysts for Fischer-Tropsch synthesis are
Iron-based and Cobalt-based catalysts, the advantage of these
catalysts on each other depends on which type of hydrocarbons we
desire to produce. In this study, Fischer-Tropsch synthesis is modeled
with Iron and Cobalt catalysts in a slurry bubble reactor considering
mass and momentum balance and the hydrodynamic relations effect
on the reactor behavior. Profiles of reactant conversion and reactant
concentration in gas and liquid phases were determined as the
functions of residence time in the reactor. The effects of temperature,
pressure, liquid velocity, reactor diameter, catalyst diameter, gasliquid
and liquid-solid mass transfer coefficients and kinetic
coefficients on the reactant conversion have been studied. With 5%
increase of liquid velocity (with Iron catalyst), H2 conversions
increase about 6% and CO conversion increase about 4%, With 8%
increase of liquid velocity (with Cobalt catalyst), H2 conversions
increase about 26% and CO conversion increase about 4%. With
20% increase of gas-liquid mass transfer coefficient (with Iron
catalyst), H2 conversions increase about 12% and CO conversion
increase about 10% and with Cobalt catalyst H2 conversions increase
about 10% and CO conversion increase about 6%. Results show that
the process is sensitive to gas-liquid mass transfer coefficient and
optimum condition operation occurs in maximum possible liquid
velocity. This velocity must be more than minimum fluidization
velocity and less than terminal velocity in such a way that avoid
catalysts particles from leaving the fluidized bed.
Abstract: In this paper, we present an experimental testing for
a new algorithm that determines an optimal controller-s coefficients
for output variance reduction related to Linear Time Invariant (LTI)
Systems. The algorithm features simplicity in calculation, generalization
to minimal and non-minimal phase systems, and could be
configured to achieve reference tracking as well as variance reduction
after compromising with the output variance. An experiment of DCmotor
velocity control demonstrates the application of this new
algorithm in designing the controller. The results show that the
controller achieves minimum variance and reference tracking for a
preset velocity reference relying on an identified model of the motor.
Abstract: In an Orthogonal Frequency Division Multiplexing (OFDM) systems, the Peak to Average power Ratio (PAR) is high. The clipping signal scheme is a useful and simple method to reduce the PAR. However, it introduces additional noise that degrades the systems performance. We propose an oversampling scheme to deal with the received signal in order to reduce the clipping noise by using Finite Impulse Response (FIR) filter. Coefficients of filter are obtained by correlation function of the received signal and the oversampling information at receiver. The performance of the proposed technique is evaluated for frequency selective channel. Results show that the proposed scheme can mitigate the clipping noise significantly for OFDM systems and in order to maintain the system's capacity, the clipping ratio should be larger than 2.5.
Abstract: Fractional delay FIR filters design method based on
the differential evolution algorithm is presented. Differential evolution
is an evolutionary algorithm for solving a global optimization problems in the continuous search space. In the proposed approach,
an evolutionary algorithm is used to determine the coefficients of
a fractional delay FIR filter based on the Farrow structure. Basic
differential evolution is enhanced with a restricted mating technique,
which improves the algorithm performance in terms of convergence
speed and obtained solution. Evolutionary optimization is carried out by minimizing an objective function which is based on the amplitude
response and phase delay errors. Experimental results show that the proposed algorithm leads to a reduction in the amplitude response and phase delay errors relative to those achieved with the Least-Squares
method.
Abstract: In this paper, we consider the almost periodic solutions of a discrete cooperation system with feedback controls. Assuming that the coefficients in the system are almost periodic sequences, we obtain the existence and uniqueness of the almost periodic solution which is uniformly asymptotically stable.
Abstract: The study of the transport coefficients in electronic
devices is currently carried out by analytical and empirical models.
This study requires several simplifying assumptions, generally
necessary to lead to analytical expressions in order to study the
different characteristics of the electronic silicon-based devices.
Further progress in the development, design and optimization of
Silicon-based devices necessarily requires new theory and modeling
tools. In our study, we use the PSO (Particle Swarm Optimization)
technique as a computational tool to develop analytical approaches in
order to study the transport phenomenon of the electron in crystalline
silicon as function of temperature and doping concentration. Good
agreement between our results and measured data has been found.
The optimized analytical models can also be incorporated into the
circuits simulators to study Si-based devices without impact on the
computational time and data storage.