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The MSE of the estimated impulse density in a multi-node system with correlated information is presented in this section.
A spectral correction gain derived using the estimated impulse responses and the noise coherence is then applied to correct the biased noise components remaining in the blocking output.
Figure 4 The estimated impulse response function of the passive path of a hearing defender with a dominant peak after 7 samples and sampling frequency 8 kHz.
The theoretical MSE of the estimated impulse density was derived for a one-node system operating in a Rayleigh fading channel.
It should however be noted that the estimated impulse responses are characterized by the shocks that appear to have persistent effects.
In Figure 4, the MSE of estimated impulse density is shown for a multi-node system using MAP detection scheme with different group sizes at the FC.
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First, we identify the tax measures that were more likely to be influenced by other macroeconomic shocks, in order to exclude them from the estimated impulse-response functions.
This paper contributes to fill this gap by estimating impulse responses to benefit reform "shocks" identified for a panel of OECD countries.
We do so by estimating impulse-response functions derived from VAR models, see Favero and Giavazzi (2012).8 Our baseline specification is a VAR of three endogenous variables: log real per capita GDP, log real per capita government spending and the short-term interest rate.
Assuming that the channel impulse response is present only within the GI, the estimated channel impulse response beyond the GI is replaced with zeros to reduce the noise [21], and an improved channel impulse response is obtained.
Figure 3 Estimated channel impulse response.
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