电竞博彩-电子竞技博彩

In this paper, the outlier-resistant recursive filtering problem is fully discussed for complex networks with time-correlated fading channels. Each sensor is able to communicate with its corresponding filter within a set of time-correlated fading channels, and the channel coefficient is assumed to be governed by certain dynamical process. In order to alleviate undesired effects (e.g. performance degradation or even divergence of the filtering error) from possible measurement outliers, a certain saturation structure is introduced in our constructed filter. The purpose is at estimating network states with satisfactory error dynamics with not only time-correlated fading channels but also measurement outliers. First, an augmented model is constructed in order to combine network dynamic evolutions along with channel coefficients. Subsequently, by means of the inductive method, upper covariance bounds are first given and later minimized by properly parameterizing filter gains. Finally, two example are given for effectiveness validation.