### Table 1. Function 1: Average RMS for random and low-discrepancy sequences.

2003

"... In PAGE 6: ... In order to construct a learning curve which shows the improvement achieved by increasing the number of training samples, the results obtained with subsets containing L = 500; 1000; 1500; 2000 and 2500 points of the basic sequences are also presented. Table1 contains the average RMS for the two kinds of sequences, computed over a flxed uniform grid of 154 = 50625 points. Training Sample size L Set 500 1000 1500 2000 2500 3000 URS 0.... ..."

Cited by 2

### Table 2: Qualitative and quantitative comparison Dataset Class Recall % Discrepancy % Evaluated

"... In PAGE 10: ... To obtain a percentage, we divide the average discrepancy by the difference of the distances of the most positive and least positive in- stances in the dataset. The results showing the per- centage of average discrepancy for all the datasets are presented in the third column of Table2 . The low values of the percentage of average discrepancy indicate that even if the retrieved instances may not exactly match the golden set of top-k instances, they are comparable in their distances from the hyperplane.... In PAGE 10: ... In other words, we were interested in finding approximately how quickly KDX converged on its set of best results. The results are reported in the fourth column of Table2 . These values are mostly very low (lower than 10%) except in the case of the smaller datasets where, because of the small size of the dataset, the percentage of evaluated samples, even with a small number of samples being evaluated, tends to be high.... ..."

### Table 1: Delay and Jitter Measurements

"... In PAGE 5: ...scilloscope. For observation and control the signal was also displayed on a monitor. With the original signal on one input channel and the delayed signal on the other channel the oscilloscope showed the time spent on the encoding and decoding process. The jitter was derived using 100 samples of measured delay values and was calculated as the difference between maximum and minimum delay within the obtained value range ( Table1 ). The indicated values include both encoding and decoding times.... ..."

### Table 4: Jitter - our scheme vs. EDCA

"... In PAGE 15: ... In our scheme, this randomness is eliminated for the high-priority streams. Continuing the study of the stationary behaviour, Table4 shows the jitter and the a10 a0 a7 a2 a12 for the high-priority stream when the number of low-priority streams is increased. We can see that the jitter is constant low for our scheme independent of the number of low-priority streams.... ..."

### Table 2: Ranking by SNR of operators on signal with no noise. Rank Stationary SNR Low Jitter SNR High Jitter SNR Dynamic SNR

"... In PAGE 11: ....2.2 Quantitative Analysis: Noise-free Sequences All of the operators degrade a noise-free sequence to a certain extent. Table2 ranks the operators in terms of SNR for each of the sequence types 2 { 4. In the stationary case, each image in the sequence is identical.... ..."

### Table 5: Discrepancies of di#0Berent sampling strategies

### TABLE XIV Maximum and mean error for different values of jitter and no. of samples.

2007

### Table 5. Arbitrary-edge discrepancies for some patterns.

1996

"... In PAGE 17: ... This process is repeated and the standard deviation of the jitter is gradually reduced. Table5 compares the resulting annealed patterns with several other interesting point patterns. The simulated annealing procedure was computationally expensive and has only been used to nd patterns of up to 64 points.... ..."

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### Table 2: Results of the verification (with the clock jitter)

2004

"... In PAGE 32: ... The symbol o denotes the SPIN answer correct , while the symbol x denotes the SPIN answer incorrect . Two tables describes the verification results with the same configuration of BPM protocol, but Table2 may express the clock jitter both in the sender and the receiver. We found that our verification results coincide with the condition (H) in the sense that if for values of code; mark; sample, and r, if SPIN says correct , then they satisfy the condition (H), but not reversely.... ..."

### Table 3: QMC results: Simulated Prices of the Asian Basket Options using Randomized Low Discrepancy Sequences

2003

"... In PAGE 9: ... This is not surprising since the rate of convergence of Monte Carlo methods does not depend on dimensions as well as the decomposed matrix ~ C. In Table3 , the same set of examples and the same techniques are compared. The only difference is that the input is drawn from the randomized Sobol0 low discrepancy sequences proposed by Owen (1995), instead of a random sequence.... ..."