Abstract: One of the main objectives of order reduction is to
design a controller of lower order which can effectively control the
original high order system so that the overall system is of lower
order and easy to understand. In this paper, a simple method is
presented for controller design of a higher order discrete system.
First the original higher order discrete system in reduced to a lower
order model. Then a Proportional Integral Derivative (PID)
controller is designed for lower order model. An error minimization
technique is employed for both order reduction and controller
design. For the error minimization purpose, Differential Evolution
(DE) optimization algorithm has been employed. DE method is
based on the minimization of the Integral Squared Error (ISE)
between the desired response and actual response pertaining to a
unit step input. Finally the designed PID controller is connected to
the original higher order discrete system to get the desired
specification. The validity of the proposed method is illustrated
through a numerical example.
Abstract: Overloading is a technique to accommodate more
number of users than the spreading factor N. This is a bandwidth
efficient scheme to increase the number users in a fixed bandwidth.
One of the efficient schemes to overload a CDMA system is to use
two sets of orthogonal signal waveforms (O/O). The first set is
assigned to the N users and the second set is assigned to the
additional M users. An iterative interference cancellation technique is
used to cancel interference between the two sets of users. In this
paper, the performance of an overloading scheme in which the first N
users are assigned Walsh-Hadamard orthogonal codes and extra users
are assigned the same WH codes but overlaid by a fixed (quasi) bent
sequence [11] is evaluated. This particular scheme is called Quasi-
Orthogonal Sequence (QOS) O/O scheme, which is a part of
cdma2000 standard [12] to provide overloading in the downlink
using single user detector. QOS scheme are balance O/O scheme,
where the correlation between any set-1 and set-2 users are
equalized. The allowable overload of this scheme is investigated in
the uplink on an AWGN and Rayleigh fading channels, so that the
uncoded performance with iterative multistage interference
cancellation detector remains close to the single user bound. It is
shown that this scheme provides 19% and 11% overloading with
SDIC technique for N= 16 and 64 respectively, with an SNR
degradation of less than 0.35 dB as compared to single user bound at
a BER of 0.00001. But on a Rayleigh fading channel, the channel
overloading is 45% (29 extra users) at a BER of 0.0005, with an SNR
degradation of about 1 dB as compared to single user performance
for N=64. This is a significant amount of channel overloading on a
Rayleigh fading channel.
Abstract: In Blind Source Separation (BSS) processing, taking
advantage of scaling factor indetermination and based on the floatingpoint
representation, we propose a scaling technique applied to the
separation matrix, to avoid the saturation or the weakness in the
recovered source signals. This technique performs an Automatic Gain
Control (AGC) in an on-line BSS environment. We demonstrate
the effectiveness of this technique by using the implementation of
a division free BSS algorithm with two input, two output. This
technique is computationally cheaper and efficient for a hardware
implementation.
Abstract: Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.
Abstract: A new fast correlation algorithm for calibrating the
wavelength of Optical Spectrum Analyzers (OSAs) was introduced
in [1]. The minima of acetylene gas spectra were measured and
correlated with saved theoretical data [2]. So it is possible to find the
correct wavelength calibration data using a noisy reference spectrum.
First tests showed good algorithmic performance for gas line spectra
with high noise. In this article extensive performance tests were made
to validate the noise resistance of this algorithm. The filter and
correlation parameters of the algorithm were optimized for improved
noise performance. With these parameters the performance of this
wavelength calibration was simulated to predict the resulting
wavelength error in real OSA systems. Long term simulations were
made to evaluate the performance of the algorithm over the lifetime
of a real OSA.
Abstract: Among various testing methodologies, Built-in Self-
Test (BIST) is recognized as a low cost, effective paradigm. Also,
full adders are one of the basic building blocks of most arithmetic
circuits in all processing units. In this paper, an optimized testable 2-
bit full adder as a test building block is proposed. Then, a BIST
procedure is introduced to scale up the building block and to generate
a self testable n-bit full adders. The target design can achieve 100%
fault coverage using insignificant amount of hardware redundancy.
Moreover, Overall test time is reduced by utilizing polymorphic
gates and also by testing full adder building blocks in parallel.
Abstract: Digital watermarking is one of the techniques for
copyright protection. In this paper, a normalization-based robust
image watermarking scheme which encompasses singular value
decomposition (SVD) and discrete cosine transform (DCT)
techniques is proposed. For the proposed scheme, the host image is
first normalized to a standard form and divided into non-overlapping
image blocks. SVD is applied to each block. By concatenating the
first singular values (SV) of adjacent blocks of the normalized image,
a SV block is obtained. DCT is then carried out on the SV blocks to
produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency
band of a SVD-DCT block by imposing a particular
relationship between two pseudo-randomly selected DCT
coefficients. An adaptive frequency mask is used to adjust local
watermark embedding strength. Watermark extraction involves
mainly the inverse process. The watermark extracting method is blind
and efficient. Experimental results show that the quality degradation
of watermarked image caused by the embedded watermark is visually
transparent. Results also show that the proposed scheme is robust
against various image processing operations and geometric attacks.
Abstract: For several high speed networks, providing resilience against failures is an essential requirement. The main feature for designing next generation optical networks is protecting and restoring high capacity WDM networks from the failures. Quick detection, identification and restoration make networks more strong and consistent even though the failures cannot be avoided. Hence, it is necessary to develop fast, efficient and dependable fault localization or detection mechanisms. In this paper we propose a new fault localization algorithm for WDM networks which can identify the location of a failure on a failed lightpath. Our algorithm detects the failed connection and then attempts to reroute data stream through an alternate path. In addition to this, we develop an algorithm to analyze the information of the alarms generated by the components of an optical network, in the presence of a fault. It uses the alarm correlation in order to reduce the list of suspected components shown to the network operators. By our simulation results, we show that our proposed algorithms achieve less blocking probability and delay while getting higher throughput.
Abstract: In this paper an algorithm for fast wavelength calibration of Optical Spectrum Analyzers (OSAs) using low power reference gas spectra is proposed. In existing OSAs a reference spectrum with low noise for precise detection of the reference extreme values is needed. To generate this spectrum costly hardware with high optical power is necessary. With this new wavelength calibration algorithm it is possible to use a noisy reference spectrum and therefore hardware costs can be cut. With this algorithm the reference spectrum is filtered and the key information is extracted by segmenting and finding the local minima and maxima. Afterwards slope and offset of a linear correction function for best matching the measured and theoretical spectra are found by correlating the measured with the stored minima. With this algorithm a reliable wavelength referencing of an OSA can be implemented on a microcontroller with a calculation time of less than one second.
Abstract: This paper describes the pipeline architecture of
high-speed modified Booth multipliers. The proposed multiplier
circuits are based on the modified Booth algorithm and the pipeline
technique which are the most widely used to accelerate the
multiplication speed. In order to implement the optimally pipelined
multipliers, many kinds of experiments have been conducted. The
speed of the multipliers is greatly improved by properly deciding the
number of pipeline stages and the positions for the pipeline registers to
be inserted. We described the proposed modified Booth multiplier
circuits in Verilog HDL and synthesized the gate-level circuits using
0.13um standard cell library. The resultant multiplier circuits show
better performance than others. Since the proposed multipliers operate
at GHz ranges, they can be used in the systems requiring very high
performance.
Abstract: In this paper, a Gaussian multiple input multiple output multiple eavesdropper (MIMOME) channel is considered where a transmitter communicates to a receiver in the presence of an eavesdropper. We present a technique for determining the secrecy capacity of the multiple input multiple output (MIMO) channel under Gaussian noise. We transform the degraded MIMOME channel into multiple single input multiple output (SIMO) Gaussian wire-tap channels and then use scalar approach to convert it into two equivalent multiple input single output (MISO) channels. The secrecy capacity model is then developed for the condition where the channel state information (CSI) for main channel only is known to the transmitter. The results show that the secret communication is possible when the eavesdropper channel noise is greater than a cutoff noise level. The outage probability is also analyzed of secrecy capacity is also analyzed. The effect of fading and outage probability is also analyzed.
Abstract: A novel robust audio watermarking scheme is
proposed in this paper. In the proposed scheme, the host audio signals
are segmented into frames. Two consecutive frames are assessed if
they are suitable to represent a watermark bit. If so, frequency
transform is performed on these two frames. The compressionexpansion
technique is adopted to generate distortion over the two
frames. The distortion is used to represent one watermark bit.
Psychoacoustic model is applied to calculate local auditory mask to
ensure that the distortion is not audible. The watermarking schemes
using mono and stereo audio signals are designed differently. The
correlation-based detection method is used to detect the distortion
and extract embedded watermark bits. The experimental results show
that the quality degradation caused by the embedded watermarks is
perceptually transparent and the proposed schemes are very robust
against different types of attacks.
Abstract: Texture information plays increasingly an important
role in remotely sensed imagery classification and many pattern
recognition applications. However, the selection of relevant textural
features to improve this classification accuracy is not a straightforward
task. This work investigates the effectiveness of two Mutual
Information Feature Selector (MIFS) algorithms to select salient
textural features that contain highly discriminatory information for
multispectral imagery classification. The input candidate features are
extracted from a SPOT High Resolution Visible(HRV) image using
Wavelet Transform (WT) at levels (l = 1,2).
The experimental results show that the selected textural features
according to MIFS algorithms make the largest contribution to
improve the classification accuracy than classical approaches such
as Principal Components Analysis (PCA) and Linear Discriminant
Analysis (LDA).
Abstract: Global Positioning System (GPS) technology is widely used today in the areas of geodesy and topography as well as in aeronautics mainly for military purposes. Due to the military usage of GPS, full access and use of this technology is being denied to the civilian user who must then work with a less accurate version. In this paper we focus on the estimation of the receiver coordinates ( X, Y, Z ) and its clock bias ( δtr ) of a fixed point based on pseudorange measurements of a single GPS receiver. Utilizing the instantaneous coordinates of just 4 satellites and their clock offsets, by taking into account the atmospheric delays, we are able to derive a set of pseudorange equations. The estimation of the four unknowns ( X, Y, Z , δtr ) is achieved by introducing an extended Kalman filter that processes, off-line, all the data collected from the receiver. Higher performance of position accuracy is attained by appropriate tuning of the filter noise parameters and by including other forms of biases.
Abstract: An adaptive spatial Gaussian mixture model is proposed for clustering based color image segmentation. A new clustering objective function which incorporates the spatial information is introduced in the Bayesian framework. The weighting parameter for controlling the importance of spatial information is made adaptive to the image content to augment the smoothness towards piecewisehomogeneous region and diminish the edge-blurring effect and hence the name adaptive spatial finite mixture model. The proposed approach is compared with the spatially variant finite mixture model for pixel labeling. The experimental results with synthetic and Berkeley dataset demonstrate that the proposed method is effective in improving the segmentation and it can be employed in different practical image content understanding applications.
Abstract: The design problem of Infinite Impulse Response (IIR)
digital filters is usually expressed as the minimization problem of
the complex magnitude error that includes both the magnitude and
phase information. However, the group delay of the filter obtained
by solving such design problem may be far from the desired group
delay. In this paper, we propose a design method of stable IIR digital
filters with prespecified maximum group delay errors. In the proposed
method, the approximation problems of the magnitude-phase and
group delay are separately defined, and these two approximation
problems are alternately solved using successive projections. As a
result, the proposed method can design the IIR filters that satisfy the
prespecified allowable errors for not only the complex magnitude but
also the group delay by alternately executing the coefficient update
for the magnitude-phase and the group delay approximation. The
usefulness of the proposed method is verified through some examples.
Abstract: The shortest path routing problem is a multiobjective
nonlinear optimization problem with constraints. This problem has
been addressed by considering Quality of service parameters, delay
and cost objectives separately or as a weighted sum of both
objectives. Multiobjective evolutionary algorithms can find multiple
pareto-optimal solutions in one single run and this ability makes them
attractive for solving problems with multiple and conflicting
objectives. This paper uses an elitist multiobjective evolutionary
algorithm based on the Non-dominated Sorting Genetic Algorithm
(NSGA), for solving the dynamic shortest path routing problem in
computer networks. A priority-based encoding scheme is proposed
for population initialization. Elitism ensures that the best solution
does not deteriorate in the next generations. Results for a sample test
network have been presented to demonstrate the capabilities of the
proposed approach to generate well-distributed pareto-optimal
solutions of dynamic routing problem in one single run. The results
obtained by NSGA are compared with single objective weighting
factor method for which Genetic Algorithm (GA) was applied.
Abstract: In this paper, we study the cooperative communications where multiple cognitive radio (CR) transmit-receive pairs competitive maximize their own throughputs. In CR networks, the influences of primary users and the spectrum availability are usually different among CR users. Due to the existence of multiple relay nodes and the different spectrum availability, each CR transmit-receive pair should not only select the relay node but also choose the appropriate channel. For this distributed problem, we propose a game theoretic framework to formulate this problem and we apply a regret-matching learning algorithm which is leading to correlated equilibrium. We further formulate a modified regret-matching learning algorithm which is fully distributed and only use the local information of each CR transmit-receive pair. This modified algorithm is more practical and suitable for the cooperative communications in CR network. Simulation results show the algorithm convergence and the modified learning algorithm can achieve comparable performance to the original regretmatching learning algorithm.
Abstract: To explore pipelines is one of various bio-mimetic
robot applications. The robot may work in common buildings such as
between ceilings and ducts, in addition to complicated and massive
pipeline systems of large industrial plants. The bio-mimetic robot finds
any troubled area or malfunction and then reports its data. Importantly,
it can not only prepare for but also react to any abnormal routes in the
pipeline. The pipeline monitoring tasks require special types of mobile
robots. For an effective movement along a pipeline, the movement of
the robot will be similar to that of insects or crawling animals. During
its movement along the pipelines, a pipeline monitoring robot has an
important task of finding the shapes of the approaching path on the
pipes. In this paper we propose an effective solution to the pipeline
pattern recognition, based on the fuzzy classification rules for the
measured IR distance data.
Abstract: Three new algorithms based on minimization of autocorrelation of transmitted symbols and the SLM approach which are computationally less demanding have been proposed. In the first algorithm, autocorrelation of complex data sequence is minimized to a value of 1 that results in reduction of PAPR. Second algorithm generates multiple random sequences from the sequence generated in the first algorithm with same value of autocorrelation i.e. 1. Out of these, the sequence with minimum PAPR is transmitted. Third algorithm is an extension of the second algorithm and requires minimum side information to be transmitted. Multiple sequences are generated by modifying a fixed number of complex numbers in an OFDM data sequence using only one factor. The multiple sequences represent the same data sequence and the one giving minimum PAPR is transmitted. Simulation results for a 256 subcarrier OFDM system show that significant reduction in PAPR is achieved using the proposed algorithms.