It is a classic problem to estimate motion-parameter of target based on bearing series in non-linear domain.
利用目标的方位序列跟踪目标的运动参数是非线性领域的一个经典问题。
Because it is not necessary to estimate the model parameter from the noisy speech, the non-parameter methods are suitable for more applications.
因为这是没有必要来估计从嘈杂的语音模型的参数，非参数方法适合于更多的应用。
A parameter estimation algorithm of chirp signal which makes use of the position and magnitude of non zero cyclic spectral peaks to estimate the three parameters is presented.
本文提出了利用非零循环频率处谱峰的位置与大小估计这三个参数的算法，该算法不需要信号参数的先验信息；
Its coordinate parameter estimate value possesses uniqueness; non - deviation and mInimum norm. Consequently. it is the most rational computing method.
其坐标参数估值具有唯一性、无偏性和最小范数性，因此，它是最合理的算法。
A new background model of non-parameter kernel density estimate was presented on the basis of abundant study on algorithms of moving object detection.
在充分研究现有运动目标检测算法的基础上，提出了一种新的非参数核密度估计背景模型。
A new background model of non-parameter kernel density estimate was presented on the basis of abundant study on algorithms of moving object detection.
在充分研究现有运动目标检测算法的基础上，提出了一种新的非参数核密度估计背景模型。
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