[ 12] We propose an ILPEF (an ILP-based algorithm for the Error Free case) algorithm which consists of two ILP formulations (ILP1 and ILP2) to deal with Problem 1.
In order to tackle the identifiability a priori, we consider the error free case where neither experimental nor model error is assumed, and explore the parameter space in order to find the viable parameter regions i.e. subsets of the parameter space where the reaction network model maintains the desired behaviour.
Similar to error-free cases, we show that the sparse principal component for the latent variables can be formulated as a bias-corrected lasso (elastic net) regression problem based on the observed surrogates, efficient algorithms are also developed to implement the procedure.
Choo and Wedley (2004), discussed 18 methods for deriving preference values from pairwise comparison matrices under a common framework of effectiveness, which is distance minimization and correctness in error-free cases.
For the error-free case, the predicted results agree with the true solutions exactly.
In addition to the ideal error-free case in which there is no difference between the experimental data and the theoretical data, the case with 5% error, in which the experimental data is simulated by adding 5% error maximum to the corresponding theoretical data, is considered for measuring error and modeling error.
While all the six methods can generate satisfactory results in error-free case, the simulation results indicate that in error case MWE (mean weighted equally) and MWAAT (mean weighted by areas of adjacent triangles) are not favorable while the other four methods exhibit no obvious difference.
The method for detecting errors using parity values is shown in Figure 2. Except for small round-off errors, the two parity values p ̄ u i and p ̄ l i should be equal in the error-free case.
It can be observed that in all cases, except in Hallmonitor, the DISCOVER codec outperforms PRISM, both in terms of PSNR in the error-free case, and in terms of quality loss in presence of channel errors.
Since the PRISM codec does not use any feedback channel, decoding failure is more frequent when the channel is error prone, which lead to a PSNR impairment, while the rate is unaltered with respect to the error-free case.
