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The thesis of this research is that a small toolbox is sufficient for a large class of symbolic applications, and that there are efficient (sequential and parallel) implementations of the toolbox.
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Each tool of the toolbox provides a stylized sequential interface, and programs that use these tools may be parallelized by using the parallel implementation of the toolbox.
FA also led implementation of the analysis toolbox in the BioUML software.
To start with, the second-order statistics of the response estimated using the available algorithms are compared in order to verify the implementations within the toolbox.
Moreover, this second part of the toolbox includes implementation tips and other useful details which may be important during the implementation phase.
Details on CVM and accuracy computing, as well as details of the toolbox used for implementation of LLE, LTSA and Isomap algorithms, are provided in Supplementary Data (paragraph 1).
The objective of the toolbox is to simplify the implementation of some optimal input design problems encountered in system identification.
The latter part of the toolbox includes specific guidance, providing details about the implementation of different measures.
In this article, we present the key functionalities of the toolbox, quantify their performance, and discuss the novel implementation of important methodological concepts concerning parameter identifiability, confidence intervals and statistical tests for model validation and discrimination.
A demonstration of the toolbox is given where the toolbox has been used for an elementary implementation of a simulation of co-evolutionary design processes.
The accuracy of the toolbox is demonstrated in [18].
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