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Application of Adaptive Filters to Active Noise Control

中国电子杂志（英文版） 2001年第4期10卷 548-551页

作者： PEI Bingnan LI Chuanguang Key Laboratory for Radar Signal Processing Xidian University Xi'an 710071 China Department of Automatic Control Beijing Institute of Technology Beijing 100081 China

A modified LMS algorithm for noise-control is suggested after a mathematical model ofsound-cancellation is established, on the basis of thesound wave interference principle and the physicalmodel of progressive waves in a duct. Its applicationin controlling noise with the frequency range from 100to 800 Hz can be implemented by using the adaptivedigital signal processing technique. The experimentson a pink noise, a broadband noise and a noise takenfrom a tank were made, which show that there existsan attenuation of 11 dB at the frequency of 500 Hzor so, and that the proposed adaptive noise controltechnique is very effective and valid.

关键词： Adaptive digital filters Active noisecontrol Digital signal processor Environmental engi-neering.

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An advanced STAP implementation for surveillance radar systems

An advanced STAP implementation for surveillance radar syste...

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11th IEEE Workshop on Statistical signal processing (SSP 2001)

作者： Fabrizio, GA Turley, MD Radar Signal Processing Group Surveillance Systems Division Defence Science and Technology Org. Canberra ACT Australia

ISBN: (纸本)0780370112

Space-time adaptive processing (STAP) has emerged as a key technology for improving the performance of radar systems required to operate in the presence of severe and dynamic interference which generally includes clutter as well as jamming. While the theory of optimum STAP is well known, practical issues such as interference heterogeneity, finite sample support, mismatched signal models and computational load need to be overcome when it comes to implementing STAP in operational radar systems. This paper proposes an advanced STAP formulation which addresses important issues facing practical implementation and then tailors this general formulation for the case of interference rejection in over-the-horizon (OTH) radar to experimentally evaluate its target detection and localisation performance.

关键词： Surveillance radar

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Data Mining and Neural Network Techniques in Case Based System

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Wuhan University Journal of Natural sciences 2001年第Z1期6卷 601-605页

作者： Ni Zhi wei 1,2 , Cai Qing sheng 1, Li Long shu 2 1.Department of Computer science, University of science and technology of China,Hefei 230027,China 2.The Key laboratory of Intelligent Computing and signal processing ,Ministry of Education Department of Computer Science University of Science and Technology of China Hefei China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

This paper first puts forward a case based system framework based on data mining techniques. Then the paper examines the possibility of using neural networks as a method of retrieval in such a case based system. In ... 详细信息

关键词： data mining neural network case based reasoning retrieval algorithm

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An advanced STAP implementation for surveillance radar systems

An advanced STAP implementation for surveillance radar syste...

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IEEE/SP Workshop on Statistical signal processing (SSP)

作者： G.A. Fabrizio M.D. Turley Radar Signal Processing Group Surveillance Systems Division Defence Science and Technology Organisation Australia

Space-time adaptive processing (STAP) has emerged as a key technology for improving the performance of radar systems required to operate in the presence of severe and dynamic interference which generally includes clutter as well as jamming. While the theory of optimum STAP is well known, practical issues, such as interference heterogeneity, finite sample support, mismatched signal models and computational load, need to be overcome when it comes to implementing STAP in operational radar systems. This paper proposes an advanced STAP formulation which addresses important issues facing practical implementation and then tailors this general formulation for the case of interference rejection in over-the-horizon (OTH) radar to evaluate experimentally its target detection and localisation performance.

关键词： Surveillance Interference Adaptive systems Space technology radar clutter Spaceborne radar Jamming Computational modeling Load modeling radar theory

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Fast principal component extraction by a homogeneous neural network

Fast principal component extraction by a homogeneous neural ...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Shan Ouyang Zheng Bao Department of Communications and Information Guilin University of Electronic and Technology Guilin Guangxi China Key Laboratory for Radar Signal Processing Xidian University Xi'an Shaanxi China

On the basis of the concepts of both weighted subspace criterion and information maximization, the paper proposes a weighted information criterion (WINC) for searching for the optimal solution of a homogeneous neural network. We develop two adaptive algorithms based on the WINC for extracting in parallel multiple principal components. Both algorithms are able to provide an adaptive step size which leads to a significant improvement in the learning performance. Furthermore, the recursive least squares version of WINC algorithms has a low computational complexity O(Np), where N is the input vector dimension and p is the number of desired principal components. Since the weighting matrix does not require an accurate value, it facilitates the system design of the WINC algorithm for real applications. Simulation results are provided to illustrate the effectiveness of WINC algorithms for PCA.

关键词： Neural networks signal processing algorithms Principal component analysis Data mining Neurons Convergence Mean square error methods Adaptive algorithm Least squares methods Resonance light scattering

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Panoramic mosaicing with image interpolation

Panoramic mosaicing with image interpolation

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International Symposium on Intelligent Multimedia, Video and Speech processing

作者： Zong-Cai Ruan Dong Liang Sui Wei Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University of Science and Technology Hefei China

ISBN: (纸本)9628576623

Panoramic mosaics methods based on an 8-parameter planar homography matrix have to overcome the accumulated errors when a sequence of images loops back on itself. Usual methods are computationally intensive, and cannot ensure complete consistency of homographies. The paper presents a simple method which does not require the consistency of homographies. The method mainly exploits an un-calibrated image perspective interpolation technique (B. Yuan et al., 1998). It is therefore simple to calculate and easy to implement.

关键词： Interpolation Transmission line matrix methods Matrix decomposition Equations Error correction Computational intelligence signal processing Nonlinear optics Optical signal processing Image motion analysis

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Local adaptive transform based image denoising with varying window size

Local adaptive transform based image denoising with varying ...

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IEEE International Conference on Image processing

作者： H. Oktem V. Katkovnik K. Egiazarin J. Astola Signal Processing Laboratory Tampere Universty of Technology Tampere Finland Department of Mechatronics Kwangju Institute of Science and Technology Kwangju Republic of Korea

Local adaptive image denoising in transform domain is a powerful tool for adapting to unknown smoothness of the images. We propose to perform local adaptive denoising with adaptively varying local transform support size rather than using a transform with fixed size. We use a special rule (intersection of confidence intervals-ICI) to select the optimum window sizes locally. The algorithm provides significant improvements in the de-noising performance.

关键词： Image denoising Noise reduction Wiener filter signal processing algorithms Filtering Wavelet domain Gaussian noise Adaptive filters Wavelet transforms Adaptive signal processing

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FAST RECURSIVE LEAST SQUARES LEARNING ALGORITHM FOR PRINCIPAL COMPONENT ANALYSIS

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Journal of Electronics(China) 2000年第3期17卷 270-278页

作者： Ouyang Shan Bao Zheng Liao Guisheng(Guilin Institute of Electronic technology, Guilin 541004)(Key laboratory of radar signal processing, Xidian Univ., Xi’an 710071) Guilin Institute of Electronic Technology Guilin Key Laboratory of Radar Signal Processing Xidian Univ. Xi’an

Based on the least-square minimization a computationally efficient learning algorithm for the Principal Component Analysis(PCA) is derived. The dual learning rate parameters are adaptively introduced to make the proposed algorithm providing the capability of the fast convergence and high accuracy for extracting all the principal components. It is shown that all the information needed for PCA can be completely represented by the unnormalized weight vector which is updated based only on the corresponding neuron input-output product. The convergence performance of the proposed algorithm is briefly *** relation between Oja’s rule and the least squares learning rule is also established. Finally, a simulation example is given to illustrate the effectiveness of this algorithm for PCA.

关键词： Neural networks Principal component analysis Auto-association Recursive least squares(RLS) learning rule

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Generalized principal ratio combining for space-time codes in slowly fading channels

Generalized principal ratio combining for space-time codes i...

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IEEE Conference on Vehicular technology (VTC)

作者： Young Ju Kim Hwang Soo Lee Signal Processing Laboratory Korea Advanced Institute of Science and Technology Daejeon South Korea

We present a generalized version of principal ratio combining (PRC) proposed by Tarokh and Lo (see IEEE Communications Letters, vol.2, p.223-25, 1998), which is a near-optimum detection scheme for space-time codes in quasistatic flat fading environments. In Tarokh et al. work, the performance penalty increases as the number of receive antennas increases. In the proposed scheme, receive antennas are divided into K groups, and the PRC detection method is applied to each group. This shows a flexible tradeoff between performance and decoding complexity by choosing the appropriate K.

关键词： Space time codes Fading Receiving antennas Decoding Partial response channels Transmitting antennas Diversity reception Space technology signal processing Laboratories

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Mobility management and routing algorithms for soft handoff in wireless mobile data network using MGCP

Mobility management and routing algorithms for soft handoff ...

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IEEE Conference on Vehicular technology (VTC)

作者： Yong-I Kim Hwang Soo Lee Signal Processing Laboratory Korea Advanced Institute of Science and Technology Daejeon South Korea

We propose a soft handoff method in packet network for CDMA mobile station and three delay constrained routing algorithms for this application that find a tree between multiple sources and multiple destinations. The proposed algorithms, which provide guaranteed QoS (quality-of-service) services at the network layer, are also designed to find reduced-cost routing trees. The proposed algorithms are verified by simulation, and three algorithms' performances are compared in view of the total tree cost and maximum end-to-end delay.

关键词： Mobile radio mobility management Routing Intelligent networks Costs Delay Multicast algorithms signal processing algorithms Multiaccess communication Tree graphs Laboratories

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