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Table 3: Scaling properties of Tildeclassic in terms of the number of examples multiplication time (CPU seconds) factor induction compilation

in unknown title
by unknown authors 1999
Cited by 35

Table 5: Scaling properties of Tilde without locality assumption, without indexing, in terms of number of examples multiplication time (CPU seconds) factor induction compilation

in unknown title
by unknown authors 1999
Cited by 35

Table 5: Performance impact of the Generalized Induction technique.

in On the Automatic Parallelization of the Perfect Benchmarks
by Rudolf Eigenmann, Jay Hoeflinger, David Padua
"... In PAGE 12: ... In #5BBE94a#5D, wehave described a new analysis technique that can handle such nonlinear subscripts. The e#0Bect of the Generalized Induction Variable transformation is shown in Table5 . The table shows the same type of information as Tables 3 and 4.... ..."

Table 1: Effects of unbalance on temperature, losses, efficiency and life time of an induction machine at rated load [11].

in H-Bridge Multilevel STATCOM for Mining Applications ∗ ABSTRACT
by Robert Betz, Ray Palmer, Terry Summers, Brian Cook, Peter Hogg
"... In PAGE 5: ...Table 1: Effects of unbalance on temperature, losses, efficiency and life time of an induction machine at rated load [11]. Table1 [11] shows the effects of various levels of imbalance on induction machines. One can see that there is a dramatic reduction in the lifetime of the machine with only 3% unbalance.... ..."

Table 5: Detailed classification of unclassified L1 misses.

in Quantifying Load Stream Behavior
by Suleyman Sair, Timothy Sherwood, Brad Calder 2002
"... In PAGE 7: ... fective address that missed in the cache. Table5 presents a detailed look into load misses that go unclassified as described above. Most of the unclassi- fied misses are recurrent pointer misses, potentially indicat- ing that the loop induction variable is updated in a non-linear fashion.... ..."
Cited by 9

Table 5: Performance impact of the Generalized Induction technique. Best loop variants are

in On the Automatic Parallelization of the Perfect Benchmarks
by Rudolf Eigenmann , Jay Hoeflinger, David Padua
"... In PAGE 12: ... In [BE94a], wehave described a new analysis technique that can handle such nonlinear subscripts. The e ect of the Generalized Induction Variable transformation is shown in Table5 . The table shows the same type of information as Tables 3 and 4.... ..."

Table 1: Voltage percent error in the non-linear low load zone with PID and PID-GMR

in Systems
by G. Cirrincione, M. Pucci, M. Cirrincione
"... In PAGE 10: ... This test has been done again, both with the PID and the PID-GMR scheme, in the linear zone of the cell characteristics and in the non-linear ones at very low and very high loads to check the improvements of the control accuracy achievable with the PID-GMR scheme. Table1 , 2, 3 show the voltage reference, the load current and the corresponding voltage percent error (difference between the reference and the real voltage) obtained with both the PID and the PID-GMR scheme respectively in the non-linear low load zone, the linear zone and the non-linear high load zone. These tables show that the PID-GMR scheme overcomes the PID one in terms of voltage error, with a resulting real voltage which better approximates the reference one.... ..."

Table 4: Elementary School Non-Linear Production Function

in Enhancing our Understanding of the Complexities of Education: "Knowledge Extraction from Data" using
by Neural Networks Bruce, Bruce D. Baker, St. Louis Mo

Table 7: Mean-Squares Error And CPU Load of Nonlinear Dynamic System

in Bayesian Estimation of Unconstrained Nonlinear Dynamic Systems via Sequential Monte Carlo Sampling
by Wen-shiang Chen, Bhavik R. Bakshi, Prem K. Goel, Sridhar Ungarala 2003
"... In PAGE 25: ...The posterior distributions shown in Figure 8 indicate the bimodal and skewed nature of the distributions. The average MSE and CPU time shown in Table7 conflrm the inability of EKF and MHE to handle such distributions. MHE performs better than EKF, but requires a great deal of computation.... ..."
Cited by 1

Table 7: Mean-squares error and CPU load of nonlinear dynamic system. EKF MHE SMC

in Bayesian Estimation via Sequential Monte Carlo Sampling- Unconstrained Nonlinear Dynamic Systems
by Wen-shiang Chen, Bhavik R. Bakshi, Prem K. Goel, Sridhar Ungarala
"... In PAGE 25: ... The posterior distributions shown in Figure 8 indicate the bimodal and skewed nature of the distributions. The average MSE and CPU time shown in Table7 conflrm the inability of EKF and MHE to handle such distributions. MHE performs better than EKF, but requires a great deal of computation.... ..."
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