ID 原文 译文
11784 高频雷达系统中,远距离扩展杂波经距离折叠后,将淹没检测区域中的目标,为保证目标的检测质量,需对折叠杂波进行抑制。 Hf radar system, the distance extension after folding clutter by distance, will be inundated area of target detection, to ensure the quality of target detection, to fold the clutter suppression.
11785 在发射二重波形重复频率信号下,提出了通过逻辑映射抑制杂波的方法。 ‭The launch of the double wave repetition frequency signal, proposed by the method of logical mapping suppress clutter.
11786 给出了参数设计准则,并分析了算法对杂波的抑制性能。 ‭Parameter design criteria are presented, and analyzed the performance of clutter suppression algorithm.
11787 仿真实验表明,在合适的信号参数下,该算法能够有效地抑制远距离折叠的扩展杂波。 ‭Simulation experiments show that under the appropriate signal parameters, the algorithm can effectively restrain the expansion of the folded over a long distance clutter. ‭
11788 在压缩感知热潮的影响下,观测矩阵的有限等距特性(restricted isometry property,RIP)也受到广泛关注。 Under the influence of compression perception boom, limited isometric characteristics of the observation matrix (restricted isometry property, RIP) have also been widespread attention.
11789 大多数理论研究表明高斯随机矩阵是满足RIP特性的,但由于其存储成本较高,物理实现较复杂,在实际使用中托普利兹(Toeplitz)随机矩阵由于可以使用快速离散傅里叶变换实现而受到青睐。 Most theoretical studies show that gaussian random matrix is to satisfy the RIP, but due to its high storage costs, physical implementation is more complex, in be used actually Toeplitz (Toeplitz) random matrix the fast discrete Fourier transform can be used to achieve and favor.
11790 该文将图论中点均匀着色定理和盖尔圆盘定理应用于压缩感知中,对托普利兹观测矩阵的RIP特性进行了证明。 In this paper, graph theory evenly coloured midpoint theorem and Gail disk set should be used to compress the perception, RIP on Toeplitz observation matrix characteristic has carried on the proof.
11791 证明结果表明,由服从某种特定概率分布的项构造的Toeplitz矩阵以较大概率满足有限等距特性。 Prove the results showed that the by obeying a certain probability distribution of term structure of Toeplitz matrices with limited isometric characteristics for large probability.
11792 最后,对最小二乘算法(least square,LS)、线性最小均方误差(linear minimum mean square error,LMMSE)算法和高斯观测矩阵的压缩感知算法以及Toeplitz观测矩阵的压缩感知算法进行了对比分析。 Finally, the least squares algorithm (further square, LS), linear minimum mean square error (linear minimum mean square error, LMMSE) algorithm and gaussian observation matrix compression perception and observation of Toeplitz matrices of compressed sensing algorithm through the contrast analysis of observation of Toeplitz matrices of compressed sensing algorithm.
11793 Toeplitz观测矩阵的压缩感知算法在性能方面要优于高斯观测矩阵的压缩感知算法和传统算法,运算复杂度方面要优于高斯随机矩阵,为压缩感知实现无失真地重构原始信号提供了理论和应用参考。 In terms of performance is better than gaussian observation matrix of compressed sensing algorithm and traditional algorithm, the computation complexity is better than gaussian random matrix, to implement undistorted compression perception to reconstruct the original signal provides the theoretical reference and application.