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For each class of activation functions, testable algebraic criteria for ascertaining global exponential periodicity and global exponential stability of a class of recurrent neural networks are derived by using the comparison principle and the theory of monotone operator.
Some sufficient criteria have been given ensuring existence, uniqueness and global exponential stability of periodic solution of a class of recurrent neural network (RNN) model by using the comparison principle, the theory of monotone flow and monotone operator.
Enrichment ratio of SDS obtained by using the spiral column was 15.7, which was 2.5 times of that obtained by using the comparison column under the suitable operating conditions of liquid loading volume 0.4 L, initial SDS concentration 0.2 g/L and superficial gas velocity 1.7 mm/s.
Again by using the comparison principle, we obtain the global existence of u x, t).
Remark 4.1 We can also easily reach our conclusion by using the comparison principle.
By using the comparison principle and inequality techniques some weaker conservative conditions are derived.
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Class comparison was performed by using the Class Comparison module of BRB ArrayTools.
Comparison of the genome sequences was facilitated by using the Artemis Comparison Tool (ACT) [26] which enabled the visualization of BLASTN and TBLASTX comparisons [14] between the genomes.
Comparison of the genome sequences was facilitated by using the Artemis Comparison Tool (ACT) [ 77], which enabled the visualization of BLASTN and TBLASTX comparisons [ 69] between the genomes.
Comparison of the genome sequences was facilitated by using the Artemis Comparison Tool (ACT) [ 91] which enabled the visualization of BLASTN and TBLASTX comparisons [ 83] between the genomes.
Comparison of the genome sequences was facilitated by using the Artemis Comparison Tool (Carver et al. 2005), which enabled the visualization of BLASTn and tBLASTx comparisons (Altschul et al. 1990) between the genomes.
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