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Table 5. Translation Time in Milliseconds for 512x512. Pixels killer mayhem mayhem1 amp;2

in unknown title
by unknown authors

Table VI. Binary Arithmetic Coding

in unknown title
by unknown authors 1995
Cited by 111

Table 5: XOR with Binary Coding

in Combining Genetic Algorithms and Neural Networks: The Encoding Problem
by Philipp Koehn
"... In PAGE 38: ... In a extended version of the first two experiments, we are looking for the optimal composition of this set. Table5 and 6 present the result of these experiments in detail, the median is printed in bold type. The results suggest that the relation between the number of mutation and crossover operators does not really matter, except that both, especially mutation, are required for an optimal use of the GANN system.... ..."

Table 5: XOR with Binary Coding

in Dedication For Claudine Acknowledgment
by unknown authors 1994
"... In PAGE 38: ... In a extended version of the first two experiments, we are looking for the optimal composition of this set. Table5 and 6 present the result of these experiments in detail, the median is printed in bold type. The results suggest that the relation between the number of mutation and crossover operators does not really matter, except that both, especially mutation, are required for an optimal use of the GANN system.... ..."

Table 5: Parameters of generalized Gray image of extended Hensel lift of QR(n) (left) and minimum distance of the best known linear codes of same length and size (right).

in unknown title
by unknown authors 2003
"... In PAGE 6: ... Following this work, we lifted generating polynomial of QR(n) for n = 17, 23, 31, 47 to Z8 and Z16, extended the resulting codes by a parity-check sym- bol, then computed their minimum distance with computer assistance. Results are shown in Table5 , bold (resp. italic) is for codes better than (resp.... ..."
Cited by 1

Table 5: Binary and Nonbinary Coding Comparison: De-

in Sequential Circuit Test Generation in a Genetic Algorithm Framework
by Elizabeth M. Rudnick, Janak H. Patel, Gary S. Greenstein, Thomas M. Niermann 1994
"... In PAGE 4: ... Signi#0Ccant di#0Berences in fault coverage were obtained for only 2 of the larger circuits, s1423 and s5378, but for those circuits, the lowest mutation rates #281#2F128 and 1#2F256#29 tended to give the highest fault coverage. Binary and nonbinary codings of test sequences are com- pared in Table5 . Results are averaged over ten runs.... ..."
Cited by 58

Table 1. Conversion of binary codes on thermometer scale

in unknown title
by unknown authors
"... In PAGE 5: ... The signals form these inputs do not carry an important information for parity problem. The binary code change on thermometer scale In this experiments the neural network converts binary code on thermometer scale as in Table1 . The input vector of neural network consists of three inputs from Table 1.... In PAGE 5: ... The binary code change on thermometer scale In this experiments the neural network converts binary code on thermometer scale as in Table 1. The input vector of neural network consists of three inputs from Table1 .and two inputs with noisy information.... ..."

Table III. Binary and octal coded elements

in Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
by F. Herrera, M. Lozano, J. L. Verdegay 1998
Cited by 68

Table IV. Comparison of binary and Gray codings

in Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
by F. Herrera, M. Lozano, J. L. Verdegay 1998
Cited by 68

Table 2: Comparison of Gray and Binary Coding

in Combining Genetic Algorithms and Neural Networks: The Encoding Problem
by Philipp Koehn
"... In PAGE 35: ... Gray coding. Table2 presents how binary and gray coding compare, if we use the median as a mea- surement. The median in this case is the result of the 25th best run out of 50 for each experi- ment.... ..."
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