论文标题
部分可观测时空混沌系统的无模型预测
Continuous Time-Delay Estimation From Sampled Measurements
论文作者
论文摘要
提出了一种从采样数据和已知的有限能量输入中进行连续时间估计的算法。连续的时间延迟建模允许估计子样本延迟。提出的估计算法包括两个步骤。首先，通过离散时间（采样）噪声测量值估计输出信号的连续拉瓜谱。其次，给定输入的连续时间描述，在Laguerre域中获得了延迟值的估计值。该算法的第二步被证明是本质上偏见的，建立了偏置源，并且对偏差本身进行了建模。在蒙特卡洛模拟中比较了提出的延迟估计方法，该模拟的时间，频率和laguerre域在被考虑的情况下显示出可比或更高的准确性。
An algorithm for continuous time-delay estimation from sampled output data and known input of finite energy is presented. The continuous time-delay modeling allows for the estimation of subsample delays. The proposed estimation algorithm consists of two steps. First, the continuous Laguerre spectrum of the output signal is estimated from discrete-time (sampled) noisy measurements. Second, an estimate of the delay value is obtained in Laguerre domain given a continuous-time description of the input. The second step of the algorithm is shown to be intrinsically biased, the bias sources are established, and the bias itself is modeled. The proposed delay estimation approach is compared in a Monte-Carlo simulation with state-of-the-art methods implemented in time, frequency, and Laguerre domain demonstrating comparable or higher accuracy for the considered case.
