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A new finite atlas of overlapping balanced canonical forms for multivariate discrete-time lossless systems is presented. The canonical forms have the property that the controllability matrix is positi...
Analyzing the data of diesel surface vibration acceleration monitoring, the method of state space reconstruction was applied. Processing the vibration acceleration signal via integration and filtering...
Approximating joint smoothing distributions using particle-based methods is a well-known issue in statistical inference when operating on general state space hidden Markov models (HMM). In this paper ...
A new framework for nonlinear system identification is presented in terms of optimal fitting of stable nonlinear state space equations to input/output/state data, with a performance objective defined ...
We consider decomposition of coordinate independent states into SO(9)×SU(2)representations in SU(2) Matrix theory. To see what and how many representations appear in the decomposition, we compute the ...
We propose the use of a state space search algorithm of the discretetime recurrent neural network to learn the short-term foreign exchange rates. By searching in the neighborhood of the target traject...
A causal input-output system may be described by a function space for inputs, a function space for outputs, and a causal operator mapping the input space into the output space. A particular representa...

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