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Voxel selection techniques can reveal important brain regions in 3-dimensional functional magnetic resonance imaging (fMRI) data analysis. In order to counteract the contamination of noise and find meaningful voxels for fMRI analysis, the sparse representation methods like Lasso have been recently proved to be efficient for voxel selection in fMRI data. However, the voxels selected by these methods...
This paper extends the norm-optimal control design methodology of iterative learning control (ILC) to the case of linear time-varying discrete repetitive processes (LTV-DRP) driven by known iteration-varying reference input signals. Our approach exploits the idea of the internal model principle for robust servomechanism design and uses a state-space model of LTV-DRPs introduced in our earlier work...
This paper deals with H∞ filtering for two-dimensional (2-D) discrete-time linear parameter-varying systems described by the Fornasini-Marchesini second model with matrices that depend rationally on convex-bounded time-varying parameters. A method is proposed for the design of robust 2-D filters with a prescribed H∞ performance for all admissible parameters' trajectories. The filter design method...
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