Sentence examples for performance of the algorithm when from inspiring English sources

The poor performance of the algorithm when using Haar wavelet is obvious in comparison to other wavelet families.

In these figures, (i) and (ii) are the performance of the algorithm when we use both algorithms together; (iii) and (iv) are when we simply use the k-means algorithm or the k-center algorithm independently.

In addition, the iterations in the algorithm have little affection for the classification performance, and when the iterations are bigger than 30, it has little effect to the performance of the algorithm when the numbers of iterations continue to increase.

The obtained gross error is relatively stable as a function of T s and τ close to the optimal value which indicates that using parameters specifically optimized for a distinct database should not critically deteriorate the performance of the algorithm when applied to other databases or in situations where an optimization of parameters is impracticable.

In Section 3.2, we benchmark the performance of the algorithm when data is generated from independent networks.

Case 3 examined the performance of the algorithm when various numbers of data points (1, 3, 5, 7, or 10) were removed to produce a smaller effective sample size n.

We also compare the performance of the algorithms when the direct links are ignored.

This is illustrated in Fig. 4 that shows the performance of the algorithms when m=3.

Figure 8 reports the performance of the algorithms when the uniform noise ids used instead of Gaussian, using the same conditions as we used before in Fig. 3.

The subsection named "Impacts produced by the early departure of clients" analyzes the performance of the algorithms when executed in scenarios with early departure of clients with the aim of demonstrating that our algorithm also shows better performance under these load conditions.

The results show superior performance of this algorithm when applied to various modulation schemes.