Abstract: This paper presents the cepstral and trispectral
analysis of a speech signal produced by normal men, men with
defective audition (deaf, deep deaf) and others affected by
tracheotomy, the trispectral analysis based on parametric methods
(Autoregressive AR) using the fourth order cumulant. These
analyses are used to detect and compare the pitches and the formants
of corresponding voiced sounds (vowel \a\, \i\ and \u\). The first
results appear promising, since- it seems after several experimentsthere
is no deformation of the spectrum as one could have supposed
it at the beginning, however these pathologies influenced the two
characteristics:
The defective audition influences to the formants contrary to the
tracheotomy, which influences the fundamental frequency (pitch).
Abstract: A wideband 2-1-1 cascaded ΣΔ modulator with a
single-bit quantizer in the two first stages and a 4-bit quantizer in the
final stage is developed. To reduce sensitivity of digital-to-analog
converter (DAC) nonlinearities in the feedback of the last stage,
dynamic element matching (DEM) is introduced. This paper presents
two modelling approaches: The first is MATLAB description and the
second is VHDL-AMS modelling of the proposed architecture and
exposes some high-level-simulation results allowing a behavioural
study. The detail of both ideal and non-ideal behaviour modelling are
presented. Then, the study of the effect of building blocks
nonidealities is presented; especially the influences of nonlinearity,
finite operational amplifier gain, amplifier slew rate limitation and
capacitor mismatch. A VHDL-AMS description presents a good
solution to predict system-s performances and can provide sensitivity
curves giving the impact of nonidealities on the system performance.
Abstract: Analyses carried out on examples of detected defects
echoes showed clearly that one can describe these detected forms according to a whole of characteristic parameters in order to be able to make discrimination between a planar defect and a volumic defect.
This work answers to a problem of ultrasonics NDT like Identification of the defects. The problems as well as the objective of
this realized work, are divided in three parts: Extractions of the parameters of wavelets from the ultrasonic echo of the detected defect - the second part is devoted to principal components analysis
(PCA) for optimization of the attributes vector. And finally to establish the algorithm of classification (SVM, Support Vector Machine) which allows discrimination between a plane defect and a
volumic defect. We have completed this work by a conclusion where we draw up a summary of the completed works, as well as the robustness of the
various algorithms proposed in this study.
Abstract: Median filters with larger windows offer greater smoothing and are more robust than the median filters of smaller windows. However, the larger median smoothers (the median filters with the larger windows) fail to track low order polynomial trends in the signals. Due to this, constant regions are produced at the signal corners, leading to the loss of fine details. In this paper, an algorithm, which combines the ability of the 3-point median smoother in preserving the low order polynomial trends and the superior noise filtering characteristics of the larger median smoother, is introduced. The proposed algorithm (called the combiner algorithm in this paper) is evaluated for its performance on a test image corrupted with different types of noise and the results obtained are included.
Abstract: Automatic Vehicle Identification (AVI) has many
applications in traffic systems (highway electronic toll collection, red
light violation enforcement, border and customs checkpoints, etc.).
License Plate Recognition is an effective form of AVI systems. In
this study, a smart and simple algorithm is presented for vehicle-s
license plate recognition system. The proposed algorithm consists of
three major parts: Extraction of plate region, segmentation of
characters and recognition of plate characters. For extracting the
plate region, edge detection algorithms and smearing algorithms are
used. In segmentation part, smearing algorithms, filtering and some
morphological algorithms are used. And finally statistical based
template matching is used for recognition of plate characters. The
performance of the proposed algorithm has been tested on real
images. Based on the experimental results, we noted that our
algorithm shows superior performance in car license plate
recognition.
Abstract: We present a novel scheme to evaluate sinusoidal functions with low complexity and high precision using cubic spline interpolation. To this end, two different approaches are proposed to find the interpolating polynomial of sin(x) within the range [- π , π]. The first one deals with only a single data point while the other with two to keep the realization cost as low as possible. An approximation error optimization technique for cubic spline interpolation is introduced next and is shown to increase the interpolator accuracy without increasing complexity of the associated hardware. The architectures for the proposed approaches are also developed, which exhibit flexibility of implementation with low power requirement.
Abstract: Most of the commonly used blind equalization algorithms are based on the minimization of a nonconvex and nonlinear cost function and a neural network gives smaller residual error as compared to a linear structure. The efficacy of complex valued feedforward neural networks for blind equalization of linear and nonlinear communication channels has been confirmed by many studies. In this paper we present two neural network models for blind equalization of time-varying channels, for M-ary QAM and PSK signals. The complex valued activation functions, suitable for these signal constellations in time-varying environment, are introduced and the learning algorithms based on the CMA cost function are derived. The improved performance of the proposed models is confirmed through computer simulations.
Abstract: To establish optical communication between any two
satellites, the transmitter satellite must track the beacon of the
receiver satellite and point the information optical beam in its
direction. Optical tracking and pointing systems for free space suffer
during tracking from high-amplitude vibration because of
background radiation from interstellar objects such as the Sun, Moon,
Earth, and stars in the tracking field of view or the mechanical
impact from satellite internal and external sources. The vibrations of
beam pointing increase the bit error rate and jam communication
between the two satellites. One way to overcome this problem is the
use of very small transmitter beam divergence angles of too narrow
divergence angle is that the transmitter beam may sometimes miss
the receiver satellite, due to pointing vibrations. In this paper we
propose the use of genetic algorithm to optimize the BER as function
of transmitter optics aperture.
Abstract: The application of a Static Synchronous Series Compensator (SSSC) controller to improve the transient stability performance of a power system is thoroughly investigated in this paper. The design problem of SSSC controller is formulated as an optimization problem and Particle Swarm Optimization (PSO) Technique is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor angle of the generator is involved; transient stability performance of the system is improved. The proposed controller is tested on a weakly connected power system subjected to different severe disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and its ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC controller improves greatly the voltage profile of the system under severe disturbances.
Abstract: In this paper the design of maximally flat linear phase
finite impulse response (FIR) filters is considered. The problem is
handled with totally two different approaches. The first one is
completely deterministic numerical approach where the problem is
formulated as a Linear Complementarity Problem (LCP). The other
one is based on a combination of Markov Random Fields (MRF's)
approach with messy genetic algorithm (MGA). Markov Random
Fields (MRFs) are a class of probabilistic models that have been
applied for many years to the analysis of visual patterns or textures.
Our objective is to establish MRFs as an interesting approach to
modeling messy genetic algorithms. We establish a theoretical result
that every genetic algorithm problem can be characterized in terms of
a MRF model. This allows us to construct an explicit probabilistic
model of the MGA fitness function and introduce the Ising MGA.
Experimentations done with Ising MGA are less costly than those
done with standard MGA since much less computations are involved.
The least computations of all is for the LCP. Results of the LCP,
random search, random seeded search, MGA, and Ising MGA are
discussed.
Abstract: In this paper, a new time-delay estimation
technique based on the cross IB-energy operator [5] is
introduced. This quadratic energy detector measures how
much a signal is present in another one. The location of the
peak of the energy operator, corresponding to the maximum of
interaction between the two signals, is the estimate of the
delay. The method is a fully data-driven approach. The
discrete version of the continuous-time form of the cross IBenergy
operator, for its implementation, is presented. The
effectiveness of the proposed method is demonstrated on real
underwater acoustic signals arriving from targets and the
results compared to the cross-correlation method.
Abstract: This study introduces a new method for detecting,
sorting, and localizing spikes from multiunit EEG recordings. The
method combines the wavelet transform, which localizes distinctive
spike features, with Super-Paramagnetic Clustering (SPC) algorithm,
which allows automatic classification of the data without assumptions
such as low variance or Gaussian distributions. Moreover, the method
is capable of setting amplitude thresholds for spike detection. The
method makes use of several real EEG data sets, and accordingly the
spikes are detected, clustered and their times were detected.
Abstract: Synchronization is a difficult problem in CDMA
satellite communications. Due to the influence of additive noise and
fading in the mobile channel, it is not easy to keep up with the
attenuation and offset. This paper considers a recently proposed
approach to solve the problem of synchronization chaotic Chen
system in CDMA satellite communication in the presence of constant
attenuation and offset. An analytic algorithm that provides closed
form channel and carrier offset estimates is presented. The principle
of this approach is based on adding a compensation block before the
receiver to compensate the distortion of the imperfect channel by
using genetic algorithm.
The resultants presented, show that the receiver is able to recover
rapidly the synchronization with the transmitter.
Abstract: A design flow of multi-standard down-conversion
CMOS mixers for three modern standards: Global System Mobile,
Digital Enhanced Cordless Telephone and Universal Mobile
Telecommunication Systems is presented. Three active mixer-s
structures are studied. The first is based on the Gilbert cell which
gives a tolerable noise figure and linearity with a low conversion
gain. The second and third structures use the current bleeding and
charge injection techniques in order to increase the conversion gain.
An improvement of about 2 dB of the conversion gain is achieved
without a considerable degradation of the other characteristics. The
models used for noise figure, conversion gain and IIP3 used are
studied. This study describes the nature of trade-offs inherent in such
structures and gives insights that help in identifying which structure
is better for given conditions.