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Blind recognition of k/n rate convolutional encoders from noisy observation 被引量:14
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作者 Li Huang Wengu Chen +1 位作者 Enhong Chen Hong Chen 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2017年第2期235-243,共9页
Blind recognition of convolutional codes is not only essential for cognitive radio, but also for non-cooperative context. This paper is dedicated to the blind identification of rate k/n convolutional encoders in a noi... Blind recognition of convolutional codes is not only essential for cognitive radio, but also for non-cooperative context. This paper is dedicated to the blind identification of rate k/n convolutional encoders in a noisy context based on Walsh-Hadamard transformation and block matrix (WHT-BM). The proposed algorithm constructs a system of noisy linear equations and utilizes all its coefficients to recover parity check matrix. It is able to make use of fault-tolerant feature of WHT, thus providing more accurate results and achieving better error performance in high raw bit error rate (BER) regions. Moreover, it is more computationally efficient with the use of the block matrix (BM) method. © 2017 Beijing Institute of Aerospace Information. 展开更多
关键词 Cognitive radio CONVOLUTION Convolutional codes Error correction Hadamard matrices Hadamard transforms linear transformations Mathematical transformations Matrix algebra Signal encoding
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Near field 3-D imaging approach for joint high-resolution imaging and phase error correction 被引量:2
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作者 Yang Fang Baoping Wang +2 位作者 Chao Sun Zuxun Song Shuzhen Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2017年第2期199-211,共13页
This paper combines compressed sensing (CS) imaging theory and range migration algorithm (RMA), and then proposes a near-field three-dimensional (3-D) imaging approach for joint high-resolution imaging and phase error... This paper combines compressed sensing (CS) imaging theory and range migration algorithm (RMA), and then proposes a near-field three-dimensional (3-D) imaging approach for joint high-resolution imaging and phase error correction. Firstly, a sparse measurement matrix construction method based on a logistic sequence is proposed, which conducts nonlinear transformation for the determined logistic sequence, making it obey uniform distribution, then conducts sign function mapping, and generates the pseudorandom sequence with Bernoulli distribution, thus leading to good signal recovery under down-sampling and easy availability for engineering realization. Secondly, in combination with the RMA imaging approach, the dictionary with all scene information and phase error correction is constructed for CS signal recovery and error correction. Finally, the non-quadratic solution model jointing imaging and phase error correction based on regularization is built, and it is solved by two steps - the separable surrogate functionals (SSF) iterative shrinkage algorithm is adopted to realize target scattering estimate; the iteration mode is adopted for the correction of the dictionary model, so as to achieve the goal of error correction and highly-focused imaging. The proposed approach proves to be effective through numerical simulation and real measurement in anechoic chamber. The results show that, the proposed approach can realize high-resolution imaging in the case of less data; the designed measurement matrix has better non-coherence and easy availability for engineering realization. The proposed approach can effectively correct the phase error, and achieve highly-focused target image. © 2017 Beijing Institute of Aerospace Information. 展开更多
关键词 Compressed sensing Error correction Image reconstruction Iterative methods linear transformations Mathematical transformations Signal reconstruction Signal sampling
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HOSVD-based LPV modeling and mixed robust H_2/H_∞ control design for air-breathing hypersonic vehicle 被引量:5
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作者 Wei Jiang Hongli Wang +1 位作者 Jinghui Lu Zheng Xie 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第1期183-191,共9页
This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying(LPV) controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition(H... This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying(LPV) controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition(HOSVD) approach.The design of hypersonic flight control systems is highly challenging due to the enormous complexity of the vehicle dynamics and the presence of significant uncertainties.Motivated by recent results on both LPV control and tensor-product(TP) model transformation approach,the velocity and altitude tracking control problems for the air-breathing hypersonic vehicle is reduced to that of a state feedback stabilizing controller design for a polytopic LPV system with guaranteed performances.The controller implementation is converted into a convex optimization problem with parameterdependent linear matrix inequalities(LMIs) constraints,which is intuitively tractable using LMI control toolbox.Finally,numerical simulation results demonstrate the effectiveness of the proposed approach. 展开更多
关键词 high order singular value decomposition(HOSVD) linear parameter varying(LPV) tensor product model transformation linear matrix inequality(LMI) air-breathing hypersonic vehicle
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