### Table 1: A summary of the equations for the time-varying rst order lter tracking algorithm.

"... In PAGE 5: ... The weighting term is of the same form, except a di erent maximum value is used, Ev. Table1 presents a summary in equation form, of the complete observer algorithm. The resulting new estimates of the state of the object are for time t ? td in the past.... ..."

### Table 7.2: Comparison of attitude simulation with closed-form solution with time-varying torques.

2003

Cited by 1

### Table 3. Econometric estimates from time-varying advertising parameter models. Variable Parameter Fluid Milk Cheese

"... In PAGE 13: ...9 and BCGW and GCGW are the brand and generic cheese advertising goodwill variables, respectively. Estimation and Testing Results Estimation results are displayed in Table3 . Before discussing those results, we need to evaluate the heteroskedastic nature of the residuals.... In PAGE 14: ... Estimation results reveal both models demonstrate reasonable explanatory power with adjusted R-square values at or above 0.94 ( Table3 ). Wald tests were constructed to test the structural heterogeneity of the advertising parameters.... In PAGE 15: ... The shorter lag-distribution for cheese relative to fluid milk is consistent with the empirical results in Kaiser that applied five-quarter lags to generic fluid milk advertising and three-quarter lags to generic cheese advertising using a polynomial distributed lag structure. Demand Elasticities Given the nonlinear specification of the time-varying parameter models, the regression results of Table3 are most usefully evaluated in terms of calculated elasticities. Table 4 provides selected elasticities for the time-varying models evaluated at the sample means.... ..."

### TABLE I 1-D DISCRETE INFINITE AND FINITE TIME AND SPACE SIGNAL PROCESSING AS FOUR INSTANTIATIONS OF THE GENERAL ALGEBRAIC THEORY. THE BOLDED CONCEPTS ARE SUPPLIED BY THE ALGEBRAIC THEORY.

2006

### Table 1: Optimiser solution times for varying continuation schemes

"... In PAGE 8: ... The use of continuation adds an extra level of robustness to the solver. Table1 compares various different continuation schemes and shows the results comparing the maximum number of processors (36) where no continuation is possible; continuation with increas- ing temperature (2 runs per processor); continuation with increasing loading (3 runs per processor); and continuation with increasing slide to roll ratio (6 runs per processor). It... ..."

Cited by 2

### Table 3. Parameter and Variable Estimates Time Invariant Time Varying (1994)

in Abstract

2007

"... In PAGE 31: ... We then use the demand equation, Equation (8), to solve for A. Table3 summarizes our parameters. 4.... ..."

### Table 5 Cycle time varying the number of trains with 11 sections

"... In PAGE 22: ... The degree of interference seems to depend on the number of sections of a circuit or, conversely, on the number of trains in a given circuit. Thus we com- puted the cycle time at varying number of sections with two trains #28Table 4#29, and at varying number of trains with 11 sections #28 Table5 #29.... In PAGE 23: ...98#25 #28for 12#29. In Table5 , it should be noted that, with increasing number of trains, the dependency makes the cycle time increase over linearly.... ..."

### Table 5: Storage requirements and elapsed solution time for vari- ous problem sizes using a complex-symmetric pro le solver (with- out pivoting) on a Sun SPARCstation10. Mesh (Unknowns) Storage (Mbytes) Solution time (min:s)

1995

"... In PAGE 26: ... very e ective for sequential machines. Table5 presents the storage requirements and elapsed times for performing direct solution of various problem sizes using a complex-symmetric pro le solver. A compar- ison of these direct solution times with iterative solution times presented in Tables 3-4 demonstrates that even for large two-dimensional problems, iterative solution using hierarchical basis preconditioners is faster by about 3 to 6 times depending on the frequency of analysis.... ..."

Cited by 8

### Table 3. The running time varying with the number of computing nodes

"... In PAGE 10: ... First we ran the original program (all pixels are processed with the simplex algorithm) on an increasing number of processors to determine how the running time and computing speed (reciprocal of running time) of the program vary with the number of processors. From Table3 we can see that, as expected, there is an approximately linear speedup with the number of processors. Since there is no interprocessor communication or search, the speedup will be approximately linear regardless of the number of processors.... ..."