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On the other hand, when the circular convolution approximation problem become severe in high reverberation, the contribution of preprocessing becomes crucial and hence the separation performance is improved significantly. Figure 12 Average relative performance improvement of the combined method over the BSS-only method in different reverberant environments.

We calculate the relative performance improvement for the 4 separation scenarios listed in Figure 11 and show the average result in Figure 12.

According to our simulations, the relative performance improvement of clustering algorithm varies between 85% and 93% for one-hop neighborhood, 234% and 313% for two-hops neighborhood, and finally 366% and 463% for three-hops neighborhood, respectively.

Here, we also observe large gains with our SE front-end, i.e., our best SE front-end achieved a relative performance improvement of 50%% over a strong DNN-based ASR back-end.

According to our simulation results, with our proposed PCAC algorithm, relative performance improvement (compared to the revised version of Kachirski et al.'s clustering algorithm) in total life time of the network varies between 85% and 93% for one-hop neighborhood, 234% and 313% for two-hops neighborhood, and finally 366% and 463% for three-hops neighborhood, respectively.

When compared to the revised version of Kachirski et al.'s clustering algorithm (see previous sub-section), relative performance improvement in TLT of the network is 93%. Figure 20 CH selection of a nine-node WSN with our algorithm; (left) at time t=0, (right) at time t=t 1(t 1>0).

However, considering the fact that the same models have been used in simulating the behavior of the baseline algorithms existing in the literature, the relative performance improvements of our proposed algorithms, presented later, are expected to hold.

The resulting relative performance improvements on the total life time of the network are as shown in Table 2. Accordingly, we conclude that, as the maximum number of hops increases, our clustering algorithm becomes more beneficial.

Table 2 Relative performance improvements on the life time of the network when our PCAC algorithm is used Maximum hops For 7-node network 9-node 15-node One-hop 86 93 85 Two-hops 234 313 256 Three-hops 366 46366366

d MRC provides the maximum performance improvement relative to all other combining techniques by maximizing the SNR of the combined signal.

The superiority of UK, RBF and OK over IDW to predict water table depth was well established by this study, but to quantify the relative performance, the per cent improvement of UK, RBF and OK over IDW was also calculated.