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Issue
1, Volume 7, January 2011
Title of the Paper:
Improved Beamspace MUSIC for Finding Directions of BPSK and QPSK Coherent
Arrivals
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Authors:
Raungrong Suleesathira, Navapol Phaisal-Atsawasenee
Abstract: Coherence is often encountered in sonar, radar or mobile
communications. Performance of the beamspace MUSIC (MUltiple Signal
Classification) deteriorates as coherent arrivals become closely space. An
improvement for the beamspace MUSIC resolution is presented. Decorrelation as
a preprocessing is performed by the techniques called forward-backward spatial
smoothing. Based on the fact that signal eigenvectors of the smoothed
correlation matrix of the received signals contains the DOA vectors, combining
all signal eigenvectors into a signal sequence enable us to obtain estimated
DOAs. This combined signal eigenvector is equivalent to an array output
impinged by the partially correlated sources. As a consequence,
forwardbackward averaging is presented to decorrelate the coherence in the
correlation matrix of the combined signal eigenvector before applying the
beamspace MUSIC to extract the DOA information. Evaluations are given to
illustrate the capability of the proposed method to distinguish closely spaced
directions and reduce estimation errors in the presence of fully correlation.
Performance analysis of BPSK and QPSK modulations are derived and compared
with the simulation results.
Keywords:
Antenna array, Beamforming, Coherent sources, Digital communication, Direction
of Arrival
Title of the Paper:
An Effective Joint Implementation Design of Channel Equalizer and DDC for
WDAR Receiver
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Authors:
Yan Jihong, Cao Gang, Xie Bin, Wu Gaokui, He Zishu
Abstract: In this paper, the technique of digital down conversion (DDC) and
channel equalization in wideband digital array radar (WDAR) are introduced.
The analysis about the frequency domain equalization algorithm based on
weighted least squares (WLS) is derived in detail at first. Then, an efficient
DDC based on polyphase structure with intermediate frequency (IF) bandpass
sampling is presented. Moreover, a simple structure which combines equalizer
and DDC is proposed, which is proven to be valid, feasible and efficient. A
design example is given and the FPGA resource consumption saving is discussed
also. The corresponding simulations and test results demonstrate the
effectiveness of the proposed DDC and show that the performance of the channel
mismatch after equalization is improved obviously.
Keywords:
Wideband digital array radar (WDAR), channel equalization, bandpass sampling,
digital down conversion (DDC), polyphase structure
Title of the Paper:
A Scalable Architecture for H.264/AVC Variable Block Size Motion Estimation
on FPGAs
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Authors:
Theepan Moorthy, Phoebe Ping Chen, Andy Ye
Abstract: In this paper, we investigate the use of Field-Programmable Gate
Arrays (FPGAs) in the design of a highly scalable Variable Block Size Motion
Estimation architecture for the H.264/AVC video encoding standard. The
scalability of the architecture allows one to incorporate the system into low
cost single FPGA solutions for low-resolution video encoding applications as
well as into high performance multi-FPGA solutions targeting high-resolution
applications. To overcome the performance gap between FPGAs and Application
Specific Integrated Circuits, our design minimizes the increase in memory
bandwidth as the design scales. The core computing unit of the architecture is
implemented on FPGAs and its performance is reported. It is shown that the
computing unit is able to achieve 58 frames per second (fps) performance for
640x480 resolution VGA video while incurring only 4.5% LUT and 6.3% DFF
utilization on a Xilinx XC5VLX330 FPGA. With 8 computing units at 38% LUT and
55% DFF utilization, the architecture is able to achieve 50 fps performance
for encoding full 1920x1088 progressive HDTV video.
Keywords:
Variable Block Size Motion Estimation, H.264/AVC, Field-Programmable Gate
Arrays
Title of the Paper:
A Fast Zigzag-Pruned 4x4 DTT Algorithm for Image Compression
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Authors:
Ranjan K. Senapati, Umesh C. Pati, Kamala K. Mahapatra
Abstract: The Discrete Tchebichef Transform (DTT) is a linear orthogonal
transform which has higher energy compactness property like other orthogonal
transform such as Discrete Cosine Transform (DCT). It is recently found
applications in image analysis and compression. This paper proposes a new
approach of fast zigzag pruning algorithm of 4x4 DTT coefficients. The
principal idea of the proposed algorithm is to make use of the distributed
arithmetic and symmetry property of 2-D DTT, which combines the similar terms
of the pruned output. Normalization of each coefficient is done by merging the
multiplication terms with the quantization matrix so as to reduce the
computation. Equal number of zigzag pruned coefficients and block pruned
coefficients are used for comparison to test the efficiency of our algorithm.
Experimental method shows that our method is competitive with the block pruned
method. Specifically for 3x3 block pruned case, our method provides lesser
computational complexity and has higher peak signal to noise ratio (PSNR). The
proposed method is implemented on a Xilinx XC2VP30 FPGA device to show its
efficient use of hardware resources.
Keywords:
Discrete Cosine Transform, Discrete- Tchebichef Transform, Image compression,
Peak signal to noise ratio, Zigzag Prune
Title of the Paper:
BiorthoganalWavelet Packets and Mel Scale Analysis for Automatic Recognition
of Arabic Speech via Radial Basis Functions
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Authors:
Jalal Karam
Abstract: In this paper, a Neural Network (NN) approach for the recognition of
the Arabic digits is presented. The two phases of training and testing in a
Radial Basis Functions (RBF) type network is described. Biorthogonal Wavelets
are constructed and used for analysis of generated subwords of the digits.
This approach decomposes spoken Arabic digits based on the acoustical
information contained within the speech signals. The procedure locates the
boundaries between subwords by finding the peaks in the function representing
the spectral changes between consecutive speech frames. The Frame-based energy
parameters derived from a Wavelet Packet Scale (WPS) are used in deriving the
Spectral Variation Function (SVF). Three Biorthogonal wavelets are used as
analyzing functions and their performances are compared with that of their
Orthogonal counterpart and with that of the traditional Fourier based Mel
scale approach.
Keywords:
Biorthogonal Wavelets, Radial Basis Functions, Recognizing Arabic Speech
Issue
2, Volume 7, April 2011
Title of the Paper:
A Modified MIMO Radar Model Based on Robustness and Gain Analysis
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Authors:
Liao Yuyu, He Zishu
Abstract: Multi-Input Multi-Output (MIMO) radar is a new radar technology in
recent years, which partially or completely uses spatial diversity gain of the
signal to replace coherent gain in traditional phased-array radar. Using the
ideal point source model, we make a detailed analysis of the contributions to
radar detection system made by these two kinds of gain. These contributions
are divided into two kinds: the contribution to system robustness and the
contribution to improving the signal-to-noise ratio. Based on this, it is
proposed that the space diversity gain of MIMO radar can make more
contribution to the system. The rationality of this proposal is further proved
by the modification of the statistical MIMO model. And the theory above is
verified by simulation. In addition, this paper illustrates how to analyze
other MIMO radar systems from the viewpoints of these two kinds of
contributions.
Keywords:
Multi-Input Multi-Output (MIMO) radar, Phased-array radar, Spatial diversity
gain, Coherent gain, Detection performance, Swerling model, Stealth target
Title of the Paper:
An Adaptive Stochastic-Resonance-Based Detector and its Application in
Watermark Extraction
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Authors:
Gencheng Guo, Mrinal Mandal
Abstract: In this paper, we explore a stochastic resonance (SR) based detector
using bistable system (BS) to detect a binary pulse amplitude modulated (PAM)
signal embedded in non-Gaussian noise. Through the example of BS based
watermark extraction, we show that a reliable performance cannot be obtained
if the BS parameters are determined by traditional tuning technique. The key
observation is that the BS parameters are not sensitive to the pdf of the
noise but to the variance of the noise and the amplitude of the signal. That
makes it possible to determine the BS parameters in advance and an adaptive BS
can be constructed based on the estimated amplitude of the watermark (signal)
and the variance of the DCT coefficients (noise). Experimental results show
that the performance obtained from the proposed adaptive
stochastic-resonator-based detector is stable and provides superior
performance compared to the existing BS based watermark schemes and the
Gaussian based maximum likelihood (ML) detector.
Keywords:
Stochastic resonance, bistable system, optimal parameters, watermark
extraction
Title of the Paper:
Intercept of Frequency Agility Signal using Coding Nyquist Folding Receiver
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Authors:
Keyu Long
Abstract: The parameter estimation of the frequency agility (FA) signal using
the coding Nyquist folding receiver (CNYFR) is presented. The estimation
algorithm adopting linear frequency modulation (LFM) as the local analogue
modulation is derived. The Nyquist zone is estimated by the pseudo
Wigner-Ville distribution (PWVD) and the hopping frequencies are calculated by
the maximum likelihood (ML) method. Simulations show that CNYFR with analogue
modulation of LFM has better performance than the sinusoidal frequency
modulation (SFM) one, and the parameter estimation accuracy is acceptable when
the SNR is above 0dB.
Keywords:
Frequency agility signal; Nyquist folding receiver; coding; linear frequency
modulation (LFM)
Issue
3, Volume 7, July 2011
Title of the Paper:
Laser Scanner Technology for Complex Surveying Structures
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Authors:
Vincenzo Barrile,Giuseppe M. Meduri, Giuliana Bilotta
Abstract: Generally, when someone refers to architectural property he inclines
to consider only that part of architecture and monuments belonging at remote
epochs far since our days. However authors’ opinion is that the diffusion and
the spreading of the culture cannot leave out from the analysis, the study and
the conservation also of architecture and all things realized in more recent
times. However, the characteristics of the modern and contemporary
architecture with respect to those precedents lead to the development of a
definition for new approaches and adequate representation forms because of the
presence both of materials and innovative technologies like the tubular or
trellis structures, that show then different difficulty in the interpretation
and definition of the acquired data. In such direction, the new digital
technologies allow, from a part, a rationalization and rapidity of the relief
operations, from the other they allow to create some new representations which
can easily fit to the scholars and operators (architects, engineers,
restorers, historians, etc) demands, or to be used to produce faithful copies
through quick prototype techniques, but also, more simply, to give back
enjoyable such information easily by town councils or web users. The developed
and described, in this article, experiences have the aim of verify the
potentialities of laser scanner in surveying of structures, for whom
traditional techniques of relief could result disadvantageous in terms of
realization’s times, costs and precision. A particular attention has addressed
to elaboration phase, data filtering and 3D modeling through the use of
specific and opportune algorithms of best-fitting, useful for
individualization and extraction of forms.
Keywords:
TLS, contemporary architecture, 3D modelization, laser scan, radiometric data,
survey
Title of the Paper:
The Use of Wavelet Entropy in Conjuction with Neural Network for Arabic
Vowels Recognition
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Authors:
W. Al-Sawalmeh, K. Daqrouq, O. Daoud
Abstract: In this research paper, Arabic vowels recognition system using very
promising techniques; wavelet packet transform (WT) with entropy and neural
network was presented. Trying to enhance the recognition process, three types
of entropies were applied for the wavelet packet (WP) of the speech signals.
Moreover, different levels of WP were used in order to enhance the efficiency
of the proposed work until level 7. To classify among the feature vectors; a
probabilistic neural network (PNN) were used. A MATLAB program was used to
build the model of the proposed work to show the powerfulness of 96.77%
identification rate. This is due to that the functions of features extraction
and classifications are performed using the entropy, wavelet packet and neural
networks.
Keywords:
Recognition, Wavelet; Entropy; Neural Network; and Arabic Vowels
Title of the Paper:
Intelligent Infrared Target for training Commandos to Combat Urban Terrorism
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Authors:
L.V. Rajani Kumari, Y. Padma Sai, N. Balaji
Abstract: The commandos are required to possess very quick reflexes for a
surprise enemy presence in combing operations particularly in terrorist’s
attacks in urban areas. Therefore, it is necessary for commandos to receive
rigorous training in environments that simulate real-life urban combat
conditions as closely as possible. In this paper, we designed an Infrared (IR)
target for commando training in urban areas. The designed system is based on
Infrared technology which will train the commando in a simulated environment
and evaluates the performance based on his response time in a given short
period. The system has Passive Infrared Sensor (PIR) and IR Transmitter
combined in one module and a microcontroller based target.
Keywords:
Commando, Infrared, Zigbee, Control Station, Passive Infrared Sensor, IR
transmitter, Target
Issue
4, Volume 7, October 2011
Title of the Paper:
Efficient Wavelet-Based Scale Invariant Features Matching
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Authors:
Shwu-Huey Yen, Nan-Chieh Lin, Hsiao-Wei Chang
Abstract: Feature points’ matching is a popular method in dealing with object
recognition and image matching problems. However, variations of images, such
as shift, rotation, and scaling, influence the matching correctness.
Therefore, a feature point matching system with a distinctive and invariant
feature point detector as well as robust description mechanism becomes the
main challenge of this issue. We use discrete wavelet transform (DWT) and
accumulated map to detect feature points which are local maximum points on the
accumulated map. DWT calculation is efficient compared to that of Harris
corner detection or Difference of Gaussian (DoG) proposed by Lowe. Besides,
feature points detected by DWT are located more evenly on texture area unlike
those detected by Harris’ which are clustered on corners. To be scale
invariant, the dominate scale (DS) is determined for each feature point.
According to the DS of a feature point, an appropriate size of region centered
at this feature point is transformed to log-polar coordinate system to improve
the rotation and scale invariance. To enhance time efficiency and illumination
robustness, we modify the contrast-based descriptors (CCH) proposed by Huang
et al. Finally, in matching stage, a geometry constraint is used to improve
the matching accuracy. Compared with existing methods, the proposed algorithm
has better performance especially in scale invariance and blurring robustness.
Keywords:
Matching, Discrete Wavelet Transform (DWT), Dominate Scale (DS), Scale
Invariance, Log-Polar Transform, Feature Point Descriptor
Title of the Paper:
Improving Speech Intelligibility in Cochlear Implants using Acoustic Models
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Authors:
P. Vijayalakshmi, T. Nagarajan, Preethi Mahadevan
Abstract: Cochlear implant (CI) is a prosthetic device that partially replaces
the functions of the human ear via electrical stimulation. Cochlear implants
are system and/or patient specific that mandates a simulation model prior to
implantation. In the present work to improve the perceptual quality of the
speech generated by a CI model, system specific parameters are analyzed by
developing uniform bandwidth filterbank-based acoustic CI models, an auditory
model-based CI system with frequency bands spacing similar to the
critical-bands of an auditory system and Mel-frequency cepstral coefficients
(MFCC) based analysis-synthesis system for cochlear implants. Acoustic CI
simulations are generated for all the vowels of English language and words
(easy and hard) from the Lexical Neighbourhood Test (LNT) and sentences from
TIMIT database using waveform and feature extraction strategies. A closed-set
listening test is conducted and a comparative study is made among the various
acoustic CI models developed. The perceptual quality/speech intelligibility of
the speech is rated in 5 point grading. It is observed that the acoustic CI
simulation for sentences generated by critical-band-based CI system showed a
mean opinion score of 4.1 as opposed to 3.1 for uniform bandwidth
filters-based CI system.
Keywords:
Cochlear implants, Filter banks, Critical band, Speech intelligibility, MFCC,
Channel vocoder, Auditory model, Acoustic CI simulations
Title of the Paper:
Handwritten Signature Identification using Basic Concepts of Graph Theory
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Authors:
Tomislav Fotak, Miroslav Baca, Petra Koruga
Abstract: Handwritten signature is being used in various applications on daily
basis. The problem arises when someone decides to imitate our signature and
steal our identity. Therefore, there is a need for adequate protection of
signatures and a need for systems that can, with a great degree of certainty,
identify who is the signatory. This paper presents previous work in the field
of signature and writer identification to show the historical development of
the idea and defines a new promising approach in handwritten signature
identification based on some basic concepts of graph theory. This principle
can be implemented on both on-line handwritten signature recognition systems
and off-line handwritten signature recognition systems. Using graph norm for
fast classification (filtration of potential users), followed by comparison of
each signature graph concepts value against values stored in database, the
system reports 94.25% identification accuracy.
Keywords:
Handwritten signature, signature recognition, identification, graph theory,
biometrics, behavioral characteristics
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