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The full-search algorithm is not realizable with the large parameters and used in Section 4.1.
This method is valid for both small and large parameters and large oscillation amplitude.
This paper addresses the problem of cascaded bistable stochastic resonance system (CBSRS) with large parameters, and reveals its non-linear low-pass filter characteristic.
First, we characterize the amplitude of the mismatch with large parameters and in order to characterize the deviation for the system setup described in Section 3. In a second step, we evaluate the end-to-end performance and the mismatch for small parameters and.
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where is a sufficiently large parameter, and where.
Perhaps such an analysis may once and for all establish the best way to choose the scheme parameters in universal fingerprinting for large parameters c and n.
This can be understood in that the latter required an extra parameter (the z-shift) to describe them, leading to a larger parameter and structure space.
Thus, there are two large parameters, namely √s/M and M/m.
Furthermore, since the POD is conducted in only one (time) dimension - with the greedy addressing the remaining (parameter) dimensions - the procedure remains computationally feasible even for large parameter domains and very extensive parameter train samples (and in particular in higher parameter dimensions).
The stochastic resonance (SR) characteristics of a single bistable system and two bistable systems connected in series with small and large parameters have been investigated, respectively.
Simulation results show that precise rotational maneuver of the spacecraft and vibration suppression in the presence of large parameter uncertainties and disturbance moment are accomplished using the L1 adaptive control law.
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