### Table 1. Summary of notation.

2004

"... In PAGE 4: ...s independent of the behavior of an MS in other intervals. This is often not the case. PEC may perform significantly better with a sleep-wake model that does not make this assumption. In addition to the above parameters, we use the notation in Table1 , which was taken from [1]. The table shows the symbol, the probability that the symbol represents, and the corresponding event.... ..."

Cited by 1

### TABLE I Comparison of some self-replicating structures in cellular space models. Models shown include variations of cellular automata: CT-machines are programmable finite automata with registers, -Universes are CAs augmented with chemistry-like operators, non-uniform CAs allow cells to have differing rules, and W-machines are Turing machine models that are programmable using high-level instructions.

1997

Cited by 18

### TABLE I Comparison of some self-replicating structures in cellular space models. Models shown include variations of cellular automata: CT-machines are programmable finite automata with registers, -Universes are CAs augmented with chemistry-like operators, non-uniform CAs allow cells to have differing rules, and W-machines are Turing machine models that are programmable using high-level instructions.

1997

Cited by 18

### Table 2: The Number of Active Elements at Time t in: Cellular Automata Without Self- Reproduction, CA(t); and Growing Automata With Self-Reproduction, GA(t): time 1s 10s 102s 103s 104s 105s

1995

"... In PAGE 7: ... Therefore, cellular automata can perform 10 steps in one second. Based on CAn and GAn, the number of active elements at time t can be calculated for cellular automata, CA(t), and for growing automata, GA(t), as follows: CA(t) = (2 (10 t) + 1)3; GA(t) = 2t=1000 ? 1: Table2 shows GA(t) and CA(t). The number of active elements in GA(t) exceeds the number of active elements in CA(t) between 104s and 105s.... ..."

Cited by 1

### Table 2: The Number of Active Elements at Time t in: Cellular Automata Without Self- Reproduction, CA(t); and Growing Automata With Self-Reproduction, GA(t): time 1s 10s 102s 103s 104s 105s

1995

"... In PAGE 7: ... Therefore, cellular automata can perform 10 steps in one second. Based on CAn and GAn, the number of active elements at time t can be calculated for cellular automata, CA(t), and for growing automata, GA(t), as follows: CA(t) = (2 (10 t) + 1)3; GA(t) = 2t=1000 ? 1: Table2 shows GA(t) and CA(t). The number of active elements in GA(t) exceeds the number of active elements in CA(t) between 104s and 105s.... ..."

Cited by 1

### Table 1. Simulation parameters for five cellular technologies.

1998

"... In PAGE 13: ... Cells were deployed in a regular hexagonal pattern of one central cluster of cells and one tier of surrounding clusters, at a spacing commensurate with high density deployment of the given technology. Table1 summarises the simulation parameters used. A cluster size of unity means that all RF channels are available in every cell.... In PAGE 15: ... Base stations were set 100p 3 m apart so that the mobile terminal range required for contiguous coverage was 100 m. The CT2 simulation parameters were as in Table1 unless otherwise indicated.... In PAGE 27: ... The two slope path loss model greatly changes the INR and cell radius distributions. The two cell, two terminal CT2 system as per Table 4 was simulated again, except with the two slope path loss model with #0D 1 = 1:5, #0D 2 = 6:0 and the path loss breakpoint b = 105 m (as per Table1 ). Figure 24 shows the theoretical INR CDF compared with an exact spill Monte Carlo simulation (both with and without shadowing of #1B = 4 dB), and Figure 25 shows the theoretical cell radius CDF compared with an exact spill Monte Carlo simulation (again with and without shadowing).... ..."

Cited by 1

### Table of partial permutivities of some elementary cellular automata.

### Table 6: Optimization for Cellular Automata Model

2005

"... In PAGE 30: ...As indicated in Table6 , there is fairly good agreement between the recommended number of booths for a typical day and for peak hours. However, we note that the optimal booth number for a typical day never exceeds that for rush hour.... In PAGE 30: ... Rush hour seems to require slightly more booths than a typical day in order for the plaza to operate most efficiently. Each value in Table6 is representative of approximately 20 trials. Through these trials, we noted a remarkable stability in our model.... ..."

### Table 1: Dynamics of Circular Elementary Cellular Automata

### Table 1Table 1 lists different pipeline techniques according to their minimal data cycle. Some of the techniques, e.g. wave-pipelining, are not applicable to SR/FIFO implementations, since they cannot be stopped by the input control signal and cannot store all internal states (some waves disappear). Wave-pipelining is latch- less technique that supports very high throughput, where only the final result at the pipeline output is sampled. The

2006

"... In PAGE 2: ...Table1 : Data Cycle Mapping For Bit-Serial Versions of Several Pipelines Name Data Cycle (# of FO4 Inv. Delays) Data Cycle (# of Transitions) Family Reference PCHB 18.... In PAGE 2: ... These numbers are scaled for FO4 inverter delays, based on the FO3 NAND delay model provided by the ITRS [18] [18]. They are used to compute data cycle in terms of the number of FO4 inverter delays in Table1 Table 1. Next, we introduce single gate-delay shift-register that meets the high-rate requirements.... ..."

Cited by 2