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		<title><![CDATA[ Signal Processing, IET - new TOC ]]></title>
		<link>http://ieeexplore.ieee.org</link>
		<description>TOC Alert for Publication# 4159607 </description>
		<year>2013</year>
		<month>May      </month>
		<day>21</day>
		<item>
			<title><![CDATA[New orthogonal polynomials for speech signal and image processing]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410947]]></link>
			<description><![CDATA[This study introduces a new set of orthogonal polynomials and moments and the set's application in signal and image processing. This polynomial is derived from two well-known orthogonal polynomials: the Tchebichef and Krawtchouk polynomials. This study attempts to present the following: (i) the mathematical and theoretical frameworks for the definition of this polynomial including the modelling of signals with the various analytical properties it contains, as well as, recurrence relations and transform equations that need to be addressed; and (ii) the results of empirical tests that compare the representational capabilities of this polynomial with those of the more traditional Tchebichef and Krawtchouk polynomials using speech and image signals from different databases. This study attempts to demonstrate that the proposed polynomials can be applied in the field of signal and image processing because of the promising properties of this polynomial especially in its localisation and energy compaction capabilities.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410947]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>713</startPage>
			<endPage>723</endPage>
			<fileSize>1028</fileSize>
			<authors><![CDATA[Jassim, W.A.;Raveendran, P.;Mukundan, R.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Improved architecture of complementary set of sequences correlation by means of an inverse generation approach]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410948]]></link>
			<description><![CDATA[System coding is a growing trend in all fields of engineering. Many different algorithms have been developed and studied for applications in signal processing, radar and multi-emission systems, among others. One of the most interesting algorithms, among these, is the complementary sets of sequences (CSS) given their potential and simplicity. They are characterised by a distinctive correlation and orthogonality properties. Nowadays, sustained efforts are being devoted to reducing the calculations involved in the generation and/or correlation of these sequences by means of recursive algorithms. Some authors have brought forward efficient algorithms that are based on modular architectures made up of adders, multipliers and delays. This work introduces an inverse generation approach to perform the correlation of CSS. This approach allows one to substantially reduce calculations, and enables the simultaneous correlation of <i>M</i> sequences, adopting neither time-multiplexing schemes nor complex parallel implementations. This is theoretically demonstrated by means of generation and correlation algorithms. An analysis of the performance and efficiency is then conducted in a reconfigurable hardware platform. The proposal represents an advance in the practical application of these sequences in the above-mentioned fields.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410948]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>724</startPage>
			<endPage>730</endPage>
			<fileSize>390</fileSize>
			<authors><![CDATA[Funes, M.A.;Donato, P.G.;Hadad, M.N.;Carrica, D.O.;Benedetti, M.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Optimal prior knowledge-based direction of arrival estimation]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410949]]></link>
			<description><![CDATA[In certain applications involving direction of arrival (DOA) estimation the operator may have a-priori information on some of the DOAs. This information could refer to a target known to be present at a certain position or to a reflection. In this study, the authors investigate a methodology for array processing that exploits the information on the known DOAs for estimating the unknown DOAs as accurately as possible. Algorithms are presented that can efficiently handle the case of both correlated and uncorrelated sources when the receiver is a uniform linear array. The authors find a major improvement in estimator accuracy in feasible scenarios, and they compare the estimator performance to the corresponding theoretical stochastic Crame&#x0301;r&#x0301;Rao bounds as well as to the performance of other methods capable of exploiting such prior knowledge. In addition, real data from an ultra-sound array is applied to the investigated estimators.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410949]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>731</startPage>
			<endPage>742</endPage>
			<fileSize>566</fileSize>
			<authors><![CDATA[Wirfa&#x0308;lt, P.;Bouleux, G.;Jansson, M.;Stoica, P.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Reliable distributed detection in multi-hop clustered wireless sensor networks]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410950]]></link>
			<description><![CDATA[The authors define the probability of receiving correct decisions from all the clusters by the data fusion centre as the reliability of distributed detection in clustered wireless sensor networks and formulate it in two cases of parallel and serial distributed detection. An energy-efficient distributed detection method - called hybrid distributed detection - is also proposed in which distributed detection is performed during hop-by-hop transmission of data from the cluster nodes to the cluster head. It is shown that this method conserves much more energy than previously proposed methods and results in considerable improvement in network reliability.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410950]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>743</startPage>
			<endPage>750</endPage>
			<fileSize>448</fileSize>
			<authors><![CDATA[Javadi, S.H.;Peiravi, A.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Movie abstraction via the progress of the storyline]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410951]]></link>
			<description><![CDATA[An appropriate movie abstraction is helpful for movie producers to promote the progress of the storyline as well as for the audiences to capture the theme of the movie before watching the full-length movie. Most existing movie abstraction schemes rely heavily on video content only, which may not deliver ideal results because of the semantic gap between computer calculated low-level audiovisual features and human used high-level perceptual understanding. In this study, the authors incorporate script into movie content understanding and present a new movie abstraction approach via the progress of the storyline, which is the soul of a film that actually catches the audiences' attention. The authors first segment the movie scenes by analysis of the movie script. Then the authors conduct storyline analysis using the attention analysis and audiovisual features. Given the transition intensity values, the authors calculate the storyline progress score and adopt this as the criterion to generate movie abstraction. The promising experimental results demonstrate that the analysis of storyline evolution is an effective approach for the abstraction and understanding of movie content.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410951]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>751</startPage>
			<endPage>762</endPage>
			<fileSize>641</fileSize>
			<authors><![CDATA[Zhu, S.;Zhao, Y.;Liang, Z.;Jing, X.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Seeker optimisation algorithm: application to the design of linear phase finite impulse response filter]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410952]]></link>
			<description><![CDATA[This study presents a novel seeker optimisation algorithm (SOA) for the design of linear phase finite impulse response low pass, high pass, band pass and band stop digital filters. A new fitness function has been adopted in order to improve the stop band attenuation, stop band ripple and to have an accurate control on the transition width. A comparison of simulation results reveals the optimisation efficacy of SOA in terms of error fitness value, stop band attenuation and stop band ripple over the prevailing optimisation techniques reported in recent literatures.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410952]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>763</startPage>
			<endPage>771</endPage>
			<fileSize>526</fileSize>
			<authors><![CDATA[Saha, S.K.;Kar, R.;Mandal, D.;Ghoshal, S.P.;]]></authors>
		</item>
		<item>
			<title><![CDATA[A novel multiple-channel active noise control approach with neural secondary-path model for interior acoustic noise attenuation of railway train systems]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410953]]></link>
			<description><![CDATA[Interior noise cancellation for railway train systems is an important means of enhancing passenger comfort and quality of service. This study proposes a novel active noise control (ANC) approach that uses an finite impulse response (IIR) filter and neural network techniques to effectively reduce interior noise. The authors construct a multiple-channel IIR filter module that is a linearly augmented framework with a generic IIR model to generate a primary control signal. A three-layer perceptron neural network is employed for establishing a secondary-path model to represent air channels among noise fields. Since the IIR module and neural network are connected in series, the output of an IIR filter is transferred forward to the neural model to generate a final ANC signal. A gradient descent optimisation-based learning algorithm is analytically derived for the optimal selection of the ANC parameter vectors. Moreover, re-estimation of partial parameter vectors in the ANC system is proposed for online learning. Sufficient stability conditions are derived for the proposed ANC system. Lastly, the authors present the results of a numerical study to test their ANC methodology with realistic interior noise measurement obtained from Korean railway trains.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410953]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>772</startPage>
			<endPage>780</endPage>
			<fileSize>839</fileSize>
			<authors><![CDATA[Cho, H.C.;Park, S.W.;Lee, K.S.;Kim, N.H.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Least squares symbol detection for two-antenna frequency hopping/M-ary frequency shift keying systems in the presence of follower jamming]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410954]]></link>
			<description><![CDATA[The jamming robustness of frequency hopping systems with <i>M</i>-ary frequency shift keying (MFSK) modulation may be potentially neutralised by a follower partial-band jammer. To remove these harmful effects, a novel detection scheme for slow frequency hopping/MFSK systems, which use two receive antennas in a quasi-static flat fading channel, is proposed. The relative complex gain factor between the two jamming components is derived and is used to aid the symbol detection process. The improved performance of the new scheme is verified by using simulated bit error rate results.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410954]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>781</startPage>
			<endPage>788</endPage>
			<fileSize>416</fileSize>
			<authors><![CDATA[Alagunarayanan, N.;Liu, F.;Ko, C.C.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Set-membership constrained conjugate gradient adaptive algorithm for beamforming]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410955]]></link>
			<description><![CDATA[In this work, a constrained adaptive filtering strategy based on conjugate gradient (CG) and set-membership techniques is presented for adaptive beamforming. A constraint on the magnitude of the array output is imposed to derive an adaptive algorithm that performs data-selective updates when calculating the beamformer's parameters. A linearly constrained minimum variance optimisation problem is consider with the bounded constraint based on this strategy and propose a CG-type algorithm for implementation. The proposed algorithm has data-selective updates, a variable forgetting factor and performs one iteration per update to reduce the computational complexity. The updated parameters construct a space of feasible solutions that enforce the constraints. The authors also introduce two time-varying bounding schemes to measure the quality of the parameters that could be included in the parameter space. A comprehensive complexity and performance analysis between the proposed and existing algorithms are provided. Simulations are performed to show the enhanced convergence and tracking performance of the proposed algorithm as compared with existing techniques.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410955]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>789</startPage>
			<endPage>797</endPage>
			<fileSize>559</fileSize>
			<authors><![CDATA[Wang, L.;de Lamare, R.C.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Speaker overlap detection with prosodic features for speaker diarisation]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410956]]></link>
			<description><![CDATA[The handling of overlapping speech in the context of speaker diarisation attracted in recent years the interest of the scientific community, since speaker overlap was identified as one of the factors degrading the performance of conventional diarisation systems. In this study, the authors are discussing the possibility of using long-term prosodic features for the detection of overlapping speech, which is subsequently employed in speaker diarisation to improve the baseline system. The most relevant subset from the set of candidate prosodic features is determined in two steps. First, a ranking according to minimal-redundancy-maximal-relevance criterion is obtained, and then a hill-climbing wrapper strategy is applied for determining the optimal number of prosodic features, which should accompany short-term spectral features for overlap detection. In experiments on the augmented multi-party interaction (AMI) meeting distant-channel data, the authors show that the addition of prosodic features decreased overlap detection error. Detected overlap segments were used in speaker diarisation to recover missed speech by assigning multiple speaker labels and to increase the purity of speaker clusters. Improvements of the baseline diarisation system are reported in both single- and multi-site data conditions. However, the extension of the diarisation system with TDOAs showed its incompatibility with the overlap exclusion technique.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410956]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>798</startPage>
			<endPage>804</endPage>
			<fileSize>403</fileSize>
			<authors><![CDATA[Zelena&#x0301;k, M.;Hernando, J.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Sample-by-sample and block-adaptive robust constant modulus-based algorithms]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410957]]></link>
			<description><![CDATA[In this study, a robust sample-by-sample linearly constrained constant modulus algorithm (LCCMA) and a robust adaptive block-Shanno constant modulus algorithm (BSCMA) are developed. The well-established quadratic inequality constraint approach is exploited to add robustness to the developed algorithms. The LCCMA algorithm is implemented using a fast steepest descent adaptive algorithm, whereas the BSCMA algorithm is realised using a modified Newton's algorithm without the inverse of Hessian matrix estimation. The developed algorithms are exercised to cancel the multiple access interference in a loaded direct sequence code division multiple access (DS/CDMA) system. Simulations are presented in a rich multipath environment with a severe near-far effect to evaluate the robustness of the proposed DS/CDMA detectors. Finally, a comprehensive comparative analysis between the sample-by-sample and block-adaptive constant modulus-based detectors is presented. It has been demonstrated that the developed robust BSCMA detector offers rapid convergence speed and very low computational complexity, whereas the developed robust LCCMA detector engenders about 5'dB improvement in the output signal-to-interference-plus-noise ratio over the BSCMA detector.]]></description>
			<pubDate><![CDATA[October  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6410957]]></guid>
			<volume>6</volume>
			<issue>8</issue>
			<startPage>805</startPage>
			<endPage>813</endPage>
			<fileSize>671</fileSize>
			<authors><![CDATA[Elnashar, A.;Elnoubi, S.;Elmikati, H.;]]></authors>
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