### Table 1. Information-theoretic analysis of grouping cues. (a) shows the results for individual features. (b) shows the results when pairs of intra- and inter- region cues are combined. The first column is the amount of information these features contain about the class label. The second column is the amount of residual information these features retain when conditioned on the model output. The marginal entropy of the class label is BDBMBC ( bits ).

2003

"... In PAGE 4: ... The distributions are normalized and the marginal entropy of CW is BDBMBC ( bits ). The first column of Table1 (a) shows the results for individ- ual features. We also combine each pair of inter- and intra- features together to evaluate the overall power of contour, texture, and brightness cues.... In PAGE 4: ... We also combine each pair of inter- and intra- features together to evaluate the overall power of contour, texture, and brightness cues. These results are listed in the first column of Table1 (b). From this analysis of mutual information we find that the presence of boundary contours is the most informative grouping cue.... In PAGE 5: ...The residual information is measured by the mutual information of CW and BY conditioned on BZ. The results have been listed in the second columns of Table1 . We observe that there is little residual information left in the features, which indi- cates that the linear classifier fits the data well.... ..."

Cited by 35

### Table 2: Learning times for QI and QS stress patterns grouped by theoretical analysis. Each figure is the average learning

1991

"... In PAGE 3: ... We claim that these results provide a source of data that can complement theoretical investigations. Table2 shows the stress systems groupedby their theoretical analyses in terms of the parameter scheme discussed in the first section. The last column of the table shows the average learningtimeinepochs foreach groupofstress patterns.... In PAGE 4: ... The result is that the second syllable receives primary stress. Under this analysis, Lakota and Polish (Group 5, in Table 2) differ from Latvian and French (Group 1 in Table2 ) only in having an extra-metrical syllable. The differing learning times for the two groups (1 epoch vs.... In PAGE 5: ... the single level of structure in Eskimo (metrical feet only.) Table2 shows that Malayalam, Yapese, Ossetic and Rotu- man (Groups 6 and 7) are the only languages withnon-iterative binary QS feet. These are also the only patterns that have more thantwo large negativeweightsgroupedtogethertothe left(for Malayalam and Ossetic) or right (for Yapese and Rotuman) of center.... In PAGE 6: ... There is a clear structural difference as compared with the (analogues of) non-iterative binary QI feet in the weights for Lakota and Polish. Komi, Cheremis, Mongolian and Mayan are the only lan- guages with non-iterative unbounded QS feet (Groups 8 and 9, Table2 ). The connection weights for these systems show a pattern of nearly-identical negative weights spanning a set of several input units, and such a pattern does not occur for any other of the stress systems.... ..."

Cited by 4

### Table 2. Overhead Analysis (Theoretical Values)

in Summary

"... In PAGE 7: ...The results of both theoretical overhead analysis ( Table2 ) and simulation study of overhead (in Figure 2) show that the impact of overhead due to update packets is not at all significant for number of nodes 60. However, with increasing number of nodes, increase in overhead is significant.... ..."

### Table 1: Comparison of different theoretical bounds for the average Hamming distance

"... In PAGE 14: ... In particular, we are interested in assessing the effectiveness of the proposed lower and upper bounds in FSM switching activity analysis and how these bounds can be used in a high-level power estimation framework. To this end, we target three sets of experiments: a) The first set of experiments shows a comparison between different theoretical bounds for average Hamming distance ( Table1 ). To do this, based on the STG of each circuit, we extract the values for the conditional and steady state probabilities for the underlying Markov chain.... In PAGE 14: ... For comparison, we also provide the simple lower bound (column 6) and the local and global lower bounds computed as in [11] (columns 7, 8). As we can see in Table1 , our best lower bound (column 4) is larger (that is, tighter) than the simple bound (column 5) which assumes that every edge is assigned a Hamming distance of 1. We also note that in some cases, the lower bound based on informational energy (column 2) is also better than the simple lower bound.... ..."

### Table 8 Theoretical analysis of Choices 5 and 11

2006

"... In PAGE 22: ... Similar results were found in separate analysis of Choices 7 and 13. A second way to analyze Choices 5 and 11, illustrated in Table8 , is to compare two classes of models. Ac- cording to prior TAX or RAM models, people should violate dominance on Choice 5 and satisfy it on Choice 11.... ..."

Cited by 3

### Table 2. However, as suggested by the theoretical analysis

"... In PAGE 6: ... Table2 . Hurs t parameter of latency for linear topology Distance from data source (in hops) 2 8 14 18 H 0.... ..."

### Table 17. Summary of (theoretical) side channel susceptibility, profile 1 candidates

"... In PAGE 26: ... Further, we provide a first intuition about the cost of protecting an implementation. Table17 summarizes the analysis results for the software candidates. It seems that the criterion exploitable (cache) timing vulnerability is best suited to categorize the candidates.... ..."

### Table 3: Rotated Component Matrix for the reduced theoretical model

"... In PAGE 12: ... The extraction method performed was Principal Component Analysis with the orthogonal Varimax rotation. The results were 5 extracted factors identical to those from the first factor analysis with 27 variables ( Table3... In PAGE 14: ...14 Table3 shows a rotated component matrix of the reduced model with 21 variables which have a high correlation (above 0.512) with the principal components of the original correlation matrix.... ..."

### Table 2. First Analysis

2005

"... In PAGE 8: ...(b). The optimization is conducted to find the minimum compliance keeping the initial volume V0 constant. Prior to discuss the optimization results structural and sensitivities analyses in the initial design is conducted to observe the performance of the RBOBM. Table2 reports the compliance results using the RBOBM approximations and FE method. As can be observed, accurate and faster results are obtained when using RBOBM.... ..."