### Table 1. RLS Heuristic Performance for Infinite Planning Horizon Case (*) System A System B System C

"... In PAGE 13: ... The RLS heuristic performance is analyzed by comparison with the optimum solution as found by the DP algorithm of Crowston, Wagner and Williams [9]. Table1 tabulates the minimum, average and maximum percent deviations from the optimum solutions among the 10 RLS heuristic replications for each problem instance. The entries in Table show that with the exception of one or two instances, even the worst of the 10 runs was substantially less than 1% away from the optimum solution for all 30 problems considered.... In PAGE 21: ...List of Tables Table1 . RLS Heuristic Performance for Infinite Planning Horizon Case Table 2.... ..."

### Table 2. Average number of implications by literals in some SAT instances from microproces- sor verification [8], infinite state system verification [9], and, other formal verification methods like BMC and equivalence checking from IBM [19], and SAT2002 suite at SATLIB [20].

"... In PAGE 5: ... The software GetAveImps to find AveImps is available at [18]. From Table2 , it can be inferred that SAT instances from Formal Verification of Microprocessors have very high AveImps value. SAT instances from other formal verification methods like ... ..."

### Tables 1-7 are for the system with infinite buffers and no RED control (studied in section 2.2). Tables 1-3 com- pare the results when the TCP or the UDP protocol is used for the probing stream. In the cross traffic we consider 1

### Table 4: Miss rates for the baseline architecture (no prefetching) and infinite SLCs.

1995

"... In PAGE 12: ...version 2.1) with optimization O2. For all measurements, we gather statistics during the parallel sections only according to the recommendations in the SPLASH report [18]. Table4 shows the cold, coherence, and total cache read miss rates for each of the applications for the baseline architecture without prefetching and with infinite SLCs. Since we assume full inclusion between the FLC and the SLC, the miss rates is calculated as the total number of read misses in the SLCs divided by the total number of read accesses to shared data in the system.... ..."

Cited by 47

### Table 2: The effect on performance when changing the distance error tolerance d. The average number of intersection points per frame is also reported. We used proximity queries on the deformable tori demo. The error determines the number of pixels used in the image-based operations. Systems with low graphics performance are more directly affected by the choice of d; however, as the error is increased there is less dependence on graphics performance and the faster laptop CPU overtakes the InfiniteReality2 system.

"... In PAGE 6: ... Average Total Per-frame Proximity Query Times Demo #Tris Isect Pts GeForce3 IR2 Rage Pro LT Cylinders 2000 513 12ms 61ms 45ms Tori 5000 1412 71 262 257 Heart 8000 317 149 329 434 Rigid 15000 2537 313 1001 966 Table 1: Performance timings for dynamics simulations. The number of triangles, average number of intersection points, and average time to run proximity queries per frame is reported for error tolerance d (see Table2 ). Timing data was gather from three machines, a Pentium4 1.... ..."

### Table 3: The effect on performance when changing the distance error tolerance d. We used proximity queries on the wavy demo with no collision response. The error determines the number of pixels used in the image- based operations. Systems with low graphics performance are more directly affected by the choice of d (see ATI Rage Pro LT); however, as the error is increased there is less dependence on graphics performance and the faster laptop CPU overtakes the InfiniteReality2 system.

### Table 1: Distortion rate performance of the following systems: the distortion rate function [15], an optimal infinite order filter bank [3], a linear phase, biorthogonal filter bank [13], an opti- mal transform coder [2], and the proposed system. N = M = 2 isused, and the source is GaussianAR(1) withcorrelation fac- tor 0.95. n0 = 2, m = 2, and l = 2.

1999

"... In PAGE 3: ... 5. COMPARISONS Table1 shows the rate distortion performance for the proposed system and some reference systems. The source to be coded is Gaussian AR(1), thus if pdf optimized scalar quantizers are used the coding constants are given by ci = p3 2 [8] for all i 2 f0; 1; : : : ; M ? 1g.... In PAGE 4: ...76 bits/sample. The same parameters as in Table1 are used. Row number i in the figure is subband number i in the subband coder.... In PAGE 4: ... However, prac- tical FIR PR systems used today do not have rate-dependent PR filter banks and the bit allocation takes care of all the rate- dependency [16]. From Table1 , it is seen that for 5.00 bits/sample, the pro- posed system achieves 0.... ..."

Cited by 3

### Table 1: Distortion rate performance of the following systems: the distortion rate function [15], an optimal infinite order filter bank [3], a linear phase, biorthogonal filter bank [13], an opti- mal transform coder [2], and the proposed system. N = M = 2 isused, and the source is GaussianAR(1) withcorrelation fac- tor 0.95. n0 = 2, m = 2, and l = 2.

1999

"... In PAGE 3: ... 5. COMPARISONS Table1 shows the rate distortion performance for the proposed system and some reference systems. The source to be coded is Gaussian AR(1), thus if pdf optimized scalar quantizers are used the coding constants are given by ci = p3 2 [8] for all i 2 f0; 1; : : : ; M ? 1g.... In PAGE 4: ...76 bits/sample. The same parameters as in Table1 are used. Row number i in the figure is subband number i in the subband coder.... In PAGE 4: ... However, prac- tical FIR PR systems used today do not have rate-dependent PR filter banks and the bit allocation takes care of all the rate- dependency [16]. From Table1 , it is seen that for 5.00 bits/sample, the pro- posed system achieves 0.... ..."

Cited by 1

### Table 1: Relation of Maximal Lyapunov Exponent and System Behaviour

"... In PAGE 21: ... Note that for a random noise, the maximal Lyapunov exponent is infinite. The summary of the system behaviour and its relation with Lyapunov exponent is shown in Table1 [8]. It should be mentioned that the Lyapunov exponent is an invariant of the system.... ..."

### Table 3. Effect of NiVER and HypBinRes Preprocessing on SAT instances from microproces- sor verification [8], infinite state system verification [9], and industrial model checking [18]. The first Siege column lists the CPU time, in seconds, taken by Siege SAT solver to solve the instance. NiVER+Siege denotes the columns concerned with experiments using NiVER pre- processor. NiVER column lists the time taken by NiVER preprocessor. The following Siege column lists the time taken to solve the NiVER simplified instances by Siege SAT solver. The total time taken by the preprocessor and solver is listed in the Total column. Similarly values are listed for HypBinRes preprocessing. Experiments were done on an Athlon 1900XP++ machine.

"... In PAGE 6: ...tag14 1071 ip38 83 cache.inv14 1940 ip50 83 Table3 , shows the effect of NiVER and HypBinRes preprocessing on SAT instances from microprocessor verification and industrial model checking. As predicted Hyp- BinRes performs well in instances with low AveImps value, while NiVER perform-... ..."