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This article is concerned with the distributed filtering problem for a class of discrete complex networks over time-varying topology described by a sequence of variables. In the developed scalable filtering algorithm, only the local information and the information from the neighboring nodes are used. As such, the proposed filter can be implemented in a truly distributed manner at each node, and it is no longer necessary to have a certain center node collecting information from all the nodes. The aim of the addressed filtering problem is to design a time-varying filter for each node such that an upper bound of the filtering error covariance is ensured and the desired filter gain is then calculated by minimizing the obtained upper bound. The filter is established by solving two sets of recursive matrix equations, and thus, the algorithm is suitable for online application. Sufficient conditions are provided under which the filtering error is exponentially bounded in mean square. The monotonicity of the filtering error with respect to the coupling strength is discussed as well. Finally, an illustrative example is presented to demonstrate the feasibility and effectiveness of our distributed filtering strategy.
This article was published in the following journal.
Name: IEEE transactions on neural networks and learning systems
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Complex sets of enzymatic reactions connected to each other via their product and substrate metabolites.
A process by which animals in various forms and stages of development are physically distributed through time and space.
A type of constriction that is caused by the presence of a fibrous ring (discrete type) below the AORTIC VALVE, anywhere between the aortic valve and the MITRAL VALVE. It is characterized by restricted outflow from the LEFT VENTRICLE into the AORTA.
An analytical transmission electron microscopy method using an electron microscope fitted with an energy filtering lens. The method is based on the principle that some of the ELECTRONS passing through the specimen will lose energy when they ionize inner shell electrons of the atoms in the specimen. The amount of energy loss is dependent upon the element. Analysis of the energy loss spectrum (ELECTRON ENERGY-LOSS SPECTROSCOPY) reveals the elemental composition of a specimen. It is used analytically and quantitatively to determine which, how much of, and where specific ELEMENTS are in a sample. For example, it is used for elemental mapping of PHOSPHORUS to trace the strands of NUCLEIC ACIDS in nucleoprotein complexes.
The ability to estimate periods of time lapsed or duration of time.