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Table 1. The truth table for the output signals of the VME bus controller example (the order of signals in the binary encodings is: dsr,

in Logic Synthesis for Asynchronous Circuits Based on Petri Net Unfoldings and Incremental SAT
by Victor Khomenko, Maciej Koutny, Alex Yakovlev 2004
Cited by 12

Table 1. The truth table for the output signals of the VME bus controller example (the order of signals in the binary encodings is: dsr,

in Logic Synthesis for Asynchronous Circuits Based on Petri Net Unfoldings and Incremental SAT
by Victor Khomenko, Maciej Koutny, Alex Yakovlev

Table II. Here, three linear output neurons are used in order to enable binary coding. Every output signal is then converted into binary digits as shown. Table III represents the data describing the new ANN used for diagnosis.

in Niš, Serbia and Montenegro
by V. Litovski, M. Andrejević

Table III. One further signal is derived from the strace logs once they had been gathered. In [14] a classification of syscalls based on the threat they pose to system security is given. Syscalls are classified as belonging to one of four levels, level 1 being the most dangerous and level 4 the least, with a number of subgroupings within each level. We implemented this by generating a binary signal whenever a syscall which belonged to level 1 is observed.

in libtissue- a Software System for Incorporating Innate Immunity into Artificial Immune Systems
by unknown authors

Table 1: Signal quality value conversion.

in unknown title
by unknown authors
"... In PAGE 28: ...5 PACKET SCHEDULING IN WIRELESS NETWORK The conversion Table1 shows the quantified signal quality value and correspond- ing binary value. Column two shows the binary signal value included in the TTL- field bits two to five.... ..."

Table 9: VT1,3-

in Key Links Systems Specification Document DOCUMENT IDENTIFIER PRESTO-W3-ACS-167b.04 Key Links Systems Specifications
by E-vod Frédéric Boudier, David Clemenceau, Patrice Fournier, Ina Jean-hugues Chenot, Denis Frambourt, Frederic Jaffres, Alain Perrier, Michel Gouley, Jean Varra, Itc/irst Roberto Brunelli, Mauro Cettolo, Jrs Gert Kienast, Kurt Majcen, Harald Mayer, Peter Schallauer, Herwig Zeiner, Ntec Maren Ernst-vogel, Robert Noll, Hans Preuschhof, Wilcox Colin Smith, Vectracom Gerard Letienne
"... In PAGE 5: ...able 8: VT1,3-Binary signals used as interruption...............................................................................52 Table9 : VT1,3-.... ..."

Table 9: VT1,3-

in Key Links Systems Specification Document DOCUMENT IDENTIFIER PRESTO-W3-ACS-167b.04 Key Links Systems Specifications
by E-vod Frédéric Boudier, David Clemenceau, Patrice Fournier, Ina Jean-hugues Chenot, Denis Frambourt, Frederic Jaffres, Alain Perrier, Michel Gouley, Jean Varra, Itc/irst Roberto Brunelli, Mauro Cettolo, Jrs Gert Kienast, Kurt Majcen, Harald Mayer, Peter Schallauer, Herwig Zeiner, Ntec Maren Ernst-vogel, Robert Noll, Hans Preuschhof, Wilcox Colin Smith, Vectracom Gerard Letienne
"... In PAGE 5: ...able 8: VT1,3-Binary signals used as interruption..........................................................................52 Table9 : VT1,3- .... ..."

Table 1: Fitness of the best individual after 100,000 function evaluations, for approximation of signal 1, using binary and real-number operators, and a population size of 100. Results averaged over 50 runs.

in Iterated Function Systems Optimization with Genetic Algorithms
by Marc M. Lankhorst, Marc M. Lankhorst
"... In PAGE 13: ...2.1 Mutation rate For a population of 100 individuals, using binary4 and real-number5 operators, and limiting the number of function evaluations to 100,000, we obtain the results shown in Table1 . This table contains the fitness (the relative L2 norm of the error) of the best individual found after 100,000 evaluations, averaged over 50 runs of the algorithm.... In PAGE 16: ...hlenbein, 1992), see Sect. 5.2.1) ensures that these parameter settings are close to the true optimum. In any case, from both Table1 and Table 2 we may infer that the use of real-number operators yields slightly better approximation results: the 95% confidence intervals do not overlap. This is illustrated in Fig.... ..."

Table 2: Fitness of the best individual after 100,000 function evaluations, for approximation of signal 1, using binary and real-number operators, and mutation rates of 0.002 and 0.05, respectively. Results averaged over 50 runs.

in Iterated Function Systems Optimization with Genetic Algorithms
by Marc M. Lankhorst, Marc M. Lankhorst
"... In PAGE 13: ...utation rate of 0.002, and for the algorithm with real-number operators, we use a rate of 0.05. Both these figures are obtained from the results given in the previous section. The results obtained are given in Table2 , which contains the fitness (the relative L2 error) of the best individual found after 100,000 function evaluations, averaged over 50 runs of the algorithm. Fig.... In PAGE 16: ...hlenbein, 1992), see Sect. 5.2.1) ensures that these parameter settings are close to the true optimum. In any case, from both Table 1 and Table2 we may infer that the use of real-number operators yields slightly better approximation results: the 95% confidence intervals do not overlap. This is illustrated in Fig.... ..."

Table 2: Prediction of Acoustic Vectors using linear prediction and binary branching HMEs with 1 and 2 levels. Prediction gain (Cuperman amp; Gersho 1985) is the ratio of the signal variance to prediction error variance.

in Non-linear Prediction of Acoustic Vectors Using Hierarchical Mixtures of Experts
by S.R. Waterhouse, A.J. Robinson
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