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SAR image despeckling combining target detection with improved nonlocal means

ELECTRONICS LETTERS 2011年第12期47卷 724-725页

作者： Zhang, W. G. Zhang, Q. Changan Univ Coll Geol Engn & Geomat Xian 710054 Peoples R China

To effectively preserve targets such as edges and dots of synthetic aperture radar (SAR) images while cleanly removing noise, a despeckling strategy is proposed. Both despeckling results of bilateral filtering and an improved nonlocal means algorithm (INLMeans) are first utilised to detect targets. Then, the detected targets are removed from the SAR image and INLMeans is employed to denoise the targets-removed image. Finally, the removed targets are added to the despeckled targets-removed image. Experimental results show that the visual quality and evaluation indexes of the proposed algorithm outperform those of the anisotropic diffusion and INLMeans.

关键词： INLMeans algorithm SAR image despeckling filtering theory synthetic aperture radar image bilateral filtering visual quality filtering methods in signal processing radar imaging anisotropic diffusion edge detection image denoising target detection improved nonlocal means algorithm Radar equipment, systems and applications synthetic aperture radar object detection Image recognition

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Extracting a source of shorter source-to-microphone distance from convolutive mixtures

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ELECTRONICS LETTERS 2011年第2期47卷 74-+页

作者： Yoo, J. K. Choi, C. H. Lee, S. Y. Korea Adv Inst Sci & Technol Div Elect Engn Taejon 305701 South Korea

Although blind source extraction is advantageous over blind signal separation in practical applications, it is difficult to choose the extracted source from many sources in the mixtures. A new algorithm is presented to extract a source signal of shorter source-to-microphone distance from two convolutive mixtures. The developed algorithm imposes an additional constraint on the extracting filters, i.e. high direct-to-reverberation ratio. In experiments, the algorithm successfully extracted the shorter-distance signal even though the interference was much stronger for both simulated convolutive mixtures and real-recorded mixtures in an office room.

关键词： filtering theory interference (signal) blind source separation Acoustic signal processing filtering methods in signal processing signal interference Architectural acoustics convolutive mixture source-to-microphone distance source signal extraction blind source extraction reverberation extracting filter direct-to-reverberation ratio microphones

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Gamma-filter self-organising neural networks for unsupervised sequence processing

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ELECTRONICS LETTERS 2011年第8期47卷 494-496页

作者： Estevez, P. A. Hernandez, R. Perez, C. A. Held, C. M. Univ Chile Dept Elect Engn Santiago 4123 Chile Univ Chile Adv Min Technol Ctr Santiago 4123 Chile

Adding gamma-filters to self-organising neural networks for unsupervised sequence processing is proposed. The proposed gamma-context model is applied to self-organising maps and neural gas networks. The gamma-context model is a generalisation that includes as a particular example the previously published merge-context model. The results show that the gamma-context model outperforms the merge-context model in terms of temporal quantisation error and state-space representation.

关键词： neural gas network filtering theory Neural nets filtering methods in signal processing unsupervised sequence processing self-organising map self-organising feature maps signal processing theory state-space representation temporal quantisation error gamma-filter self-organising neural network merge-context model

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Multi-baseline phase unwrapping algorithm based on the unscented Kalman filter

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IET RADAR SONAR AND NAVIGATION 2011年第3期5卷 296-304页

作者： Xianming, X. Yiming, P. Univ Elect Sci & Technol China Sch Elect Engn Chengdu Peoples R China

A new multi-baseline phase unwrapping algorithm based on the unscented Kalman filter (UKF) for SAR interferometry is proposed. This method is the result of combining a UKF with a path-following strategy and an omnidirectional local phase slope estimator. This technology simultaneously performs noise filtering and phase unwrapping by an optimal data fusion approach. In addition, phase slope will be directly estimated from the sample frequency spectrum of the complex interferogram, by which the underestimation of phase slope is overcome. Results obtained with synthetic and real data validate the effectiveness of the proposed method.

关键词： unscented Kalman filter noise filtering SAR interferometry radar interferometry filtering methods in signal processing multibaseline phase unwrapping algorithm Geophysical techniques and equipment omni-directional local phase slope estimator sample frequency spectrum path-following strategy sensor fusion synthetic aperture radar Kalman filters Radar equipment, systems and applications optimal data fusion approach

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Particle filter to track multiple people for visual surveillance

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IET COMPUTER VISION 2011年第4期5卷 192-200页

作者： Sherrah, J. Ristic, B. Redding, N. J. Def Sci & Technol Org ISR Div Port Melbourne Vic 3207 Australia Def Sci & Technol Org ISR Div Edinburgh SA 5111 Australia

A particle filter (PF) has been recently proposed to detect and track colour objects in video. This study presents an adaptation of the PF to track people in surveillance video. Detection is based on automated background modelling rather than a manually generated object colour model. Furthermore, a labelling method is proposed to create tracks of objects through the scene, rather than unconnected detections. A methodical comparison between the new PF tracking method and two other multi-object trackers is presented on the PETS 2004 benchmark data set. The PF tracker gives significantly fewer false alarms owing to explicit modelling of the object birth and death processes, while maintaining a good detection rate.

关键词： object tracking video surveillance labelling method Video signal processing particle filtering (numerical methods) visual surveillance object detection PETS 2004 benchmark data set multiobject trackers object colour model Optical, image and video signal processing particle filter filtering methods in signal processing image colour analysis PF tracking method

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Kalman smoothing-based adaptive frequency-domain channel estimation for uplink multiple-input multiple-output orthogonal frequency division multiple access systems

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IET COMMUNICATIONS 2011年第2期5卷 199-208页

作者： Gao, J. Zhu, X. Wu, Y. Nandi, A. K. Univ Liverpool Dept Elect Engn & Elect Liverpool L69 3GJ Merseyside England

This study investigates Kalman smoothing (KS)-based frequency-domain channel estimation for uplink multiple-input multiple-output (MIMO) orthogonal frequency division multiple access (OFDMA) systems with time-varying channels. The proposed KS channel estimation scheme significantly outperforms the recursive least squares (RLS) channel estimation in the high signal-to-noise ratio (SNR) range, because of more effective exploitation of the signal information. In addition, channel interpolation is employed to improve the channel estimation accuracy by exploiting the correlation between adjacent subcarriers. The proposed KS channel estimator can also achieve a bit error rate (BER) performance which is close to the case with perfect channel state information (CSI) with a training overhead of only 5%.

关键词： recursive estimation bit error rate error statistics least mean squares methods signal to noise ratio channel interpolation Modulation and coding methods MIMO OFDM modulation time-varying channels channel estimation recursive least squares Multiple access communication adaptive Kalman smoothing multiple input multiple output filtering methods in signal processing Mathematical analysis frequency-domain analysis frequency division multiple access adaptive Kalman filters Interpolation and function approximation (numerical analysis) orthogonal frequency division multiple access system Radio links and equipment channel state information Communication channel equalisation and identification OFDMA system MIMO communication Other topics in statistics

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Tunable coplanar waveguide band-stop and band-pass filters based on open split ring resonators and open complementary split ring resonators

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IET MICROWAVES ANTENNAS & PROPAGATION 2011年第3期5卷 277-281页

作者： Velez, A. Aznar, F. Duran-Sindreu, M. Bonache, J. Martin, F. Univ Autonoma Barcelona Dept Elect Engn E-08193 Barcelona Spain

In this study, the authors show that open split ring resonators (OSRRs) and open complementary split ring resonators (OCSRRs) can be loaded with varactor diodes in order to implement tunable filters in coplanar waveguide (CPW) technology. By loading a CPW with shunt-connected varactor-loaded OSRRs, a band-stop filter with tunable central frequency results. The electronically tunable band stop can be switched to a pass band by replacing the shunt resonators with varactor-loaded OCSRRs. To illustrate the possibilities of the approach, a tunable band-stop filter and a tunable band-pass filter have been designed and fabricated. The measured characteristics are in good agreement with the co-simulations (electric and electromagnetic) and with the circuit simulations of the electric model. The measured tuning range is roughly 120% for the stop-band structure (for varying voltages between 0 and 28 V) and over 30% for the band-pass filter (for varying voltages between 5 and 25 V).

关键词： filtering methods in signal processing Waveguides and microwave transmission lines tunable filters resonator filters open split ring resonators coplanar waveguides varactor diodes tunable coplanar waveguide Capacitors varactors Waveguide and microwave transmission line components open complementary split ring resonators band-pass filters band-stop filters

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Modified RLS algorithm with enhanced tracking capability for MIMO channel estimation

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ELECTRONICS LETTERS 2011年第19期47卷 1101-1102页

作者： Arablouei, R. Dogancay, K. Univ S Australia Inst Telecommun Res Mawson Lakes SA Australia Univ S Australia Sch Elect & Informat Engn Mawson Lakes SA Australia

A new RLS adaptive filtering algorithm has been developed by enforcing a constraint on the a posteriori error of the conventional exponentially-weighted RLS algorithm and modifying its coefficient update equation. The motivation behind the new algorithm is to attain improved tracking capability when the target system features fast variations in time. The proposed algorithm requires only slightly more computations than the conventional RLS algorithm and is specifically suitable for estimation and tracking of fast-fading MIMO channels. Simulations demonstrate that a MIMO channel estimator utilising the proposed algorithm outperforms those using the conventional RLS algorithm, the set-membership-based BEACON algorithm and the extended RLS algorithm without requiring prior knowledge of the Doppler shift.

关键词： Communication channel equalisation and identification fast-fading MIMO channel estimation set-membership-based BEACON algorithm conventional exponentially-weighted RLS algorithm filtering methods in signal processing adaptive filters channel estimation fading channels RLS adaptive filtering algorithm Doppler shift MIMO communication Radio links and equipment tracking capability

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Statistical-mechanics approach to the filtered-X LMS algorithm

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ELECTRONICS LETTERS 2011年第17期47卷 997-U83页

作者： Miyoshi, S. Kajikawa, Y. Kansai Univ Fac Engn Sci Suita Osaka Japan

The learning curves of the filtered-X least-mean-square (LMS) algorithm are theoretically obtained using a statistical-mechanics approach. The direction cosines among the vectors of an adaptive filter, its shifted filters, and an unknown system are treated as macroscopic variables. Assuming that the tapped-delay line is sufficiently long, simultaneous differential equations are obtained that describe the dynamical behaviours of the macroscopic variables in a deterministic form. The equations are solved analytically and show that the obtained theory quantitatively agrees with computer simulations. In the analysis, neither the independence assumption nor the few-taps assumption is used.

关键词： differential equations Pulse circuits digital filters Interpolation and function approximation (numerical analysis) signal processing theory Differential equations (numerical analysis) Digital filters Acoustic signal processing macroscopic variables direction cosines filtered-X LMS algorithm filtering methods in signal processing statistical mechanics approach adaptive filter delay lines tapped-delay line differential equation filtered-X least mean square algorithm statistical mechanics least mean squares methods

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Voice conversion using support vector regression

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ELECTRONICS LETTERS 2011年第18期47卷 1045-U1586页

作者： Song, P. Bao, Y. Q. Zhao, L. Zou, C. R. Southeast Univ Key Lab Underwater Acoust Signal Proc Minist Educ Nanjing 210096 Peoples R China

A new voice conversion method based on support vector regression (SVR) is proposed, and the mapping abilities of a multi-dimensional SVR are exploited to perform the mapping of spectral features of a source speaker to that of a target speaker. A novel mixed kernel is presented to improve the mapping performance, the correlations between frames of the source speaker are considered to overcome the discontinuities of converted speech, and an adaptive median filter is adopted in the conversion phase to smooth the converted spectral parameter trajectory. Experimental results show that the proposed method outperforms the state-of-the-art Gaussian mixture model based method, it can achieve high similarity between converted and target speakers, and has good quality and naturalness.

关键词： Speech processing techniques SVR mapping performance adaptive median filter filtering methods in signal processing regression analysis adaptive filters support vector machines voice conversion median filters source speaker target speaker Other topics in statistics Speech recognition and synthesis speech synthesis Gaussian mixture model support vector regression Gaussian processes

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