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IMPROVEMENT OF HIDDEN MARKOV MODEL EVALUATION OF THE MOBILE SATELLITE CHANNEL BY RESORTING TO A TRANSITION LOCALISATION METHOD

机译:通过借鉴转换定位方法,改善移动卫星信道的隐马尔可夫模型评估

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The mobile satellite channel has underlying Markovian properties and can then be represented by a Hidden Markov model (HMM). A challenging problem consists in estimating the model parameters from experimental data, especially when these parameters are not easily identifiable. In these cases, classification methods like k-means or scalable clustering, which are considered in this paper, show poor results when applied to the channel signal directly. We show that the detection of change-points of the signal, i.e. the detection of transitions between the model states, in a preliminary step, improves the estimation of the model parameters. We thus propose a method of model estimation including the detection of change-points that enables a better modelling of the satellite channel.
机译:移动卫星频道具有底层的马尔可夫属性,然后可以由隐藏的马尔可夫模型(HMM)表示。 一个具有挑战性的问题在于估计来自实验数据的模型参数,尤其是当这些参数不容易识别时。 在这些情况下,在本文中考虑的k-means或可扩展聚类等分类方法,当直接施加到信道信号时,效果差。 我们表明,检测信号的变化点,即模型状态之间的转换,在初步步骤中,提高了模型参数的估计。 因此,我们提出了一种模型估计的方法,包括检测改变点,这使得能够更好地建模卫星信道。

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