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Step 4: Asymptotic stability of the filter.
Next, let us consider the stability of the filter error system (6).
Energy resolution, beam shape and stability of the filter have been measured.
Outcomes were comparable in the two groups with respect to mechanical stability of the filter.
It is proved that stability of the filter can be achieved under sufficiently high bit rate even for unstable systems.
This formulation guarantees stability of the filter itself and will enhance overall computational stability in a full wave model.
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Next, we discuss the stability of the filtering error system (5) with (w(t) = 0), which is equivalent to the stability of the filtering error system (5) without (w(t)).
Filter banks are traditionally composed of finite or infinite response filters in principle [14], but the stability of the filters is usually difficult to be guaranteed.
Based on this model, sufficient conditions of the mean square stability of the filtering error system and H∞ filter parameters are achieved.
A new performance characterization is first established to guarantee the asymptotic stability of the filtering error system with the ℓ1-induced performance.
A stochastic L2 L∞ filter which guarantees asymptotic mean-square stability of the filtering error system is designed in terms of LMIs.
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