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Theory and Modern Applications

Table 1 The values of estimator gain \(K_{k}\)

From: Variance-constrained resilient \(H_{\infty }\) state estimation for time-varying neural networks with randomly varying nonlinearities and missing measurements

k

\(K_{k}\)

1

\(K_{1}=[ -0.1701 \ 0.1102 ]^{T}\)

2

\(K_{2}=[ -0.1481 \ 0.2838 ]^{T}\)

3

\(K_{3}=[ -0.2438 \ 0.1024 ]^{T}\)