Since in this process, raw material costs play a more decisive role as compared to the costs of procedure, the optimization aims at raw material saving that corresponds to a small value of basis weight of the non-woven, while quality assurance.
In order to overcome this problem, a reasonably small value of the weighting factor should be selected to achieve good performance at the expense of slow convergence rate.
As expected, the Morozov-LPIC detector exhibits the best average BER performance for small values of the weighting factor (β = 2).
Similar to the AWGN channel, using relatively small values of the weighting factor enhances the performance of the Morozov-LPIC detector, however, this results in a very slow convergence rate.
High expression profile similarity among genes with common functional annotation results in small values of their weights and consequently in tight clusters.
This small value received for wine exports will buy only a small value of cloth imports.
The number of nonzero β ^ j is controlled directly through λ; small values of λ result in low weight to the L1-norm penalty and therefore many nonzero β ^ j estimates, or many variables being selected, and as λ increases, so does the weight of the penalty.
A larger value of w gives more weight to the initial composition, while a smaller value of w gives more weight to the ultimate stable fraction.
Mathematically, this can be understood by noting that the expected sequence quality Q* is determined not by the arithmetic mean of the basewise quality scores, but by a generalized f-mean with <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0017034.e001.PNG" class= inline-graphic"/>, which gives large weight to small values of q.
Large values of T (high stringency) is appropriate for gene expression [ 15], while small values of T (low stringency) increase the weighting of subtle differences in expression, and may be required to discriminate arrays at the pathway level, where the coordinated effects of multiple genes are under consideration.
The second term on the right hand side of (5), known as weight decay, favors small values of w and decreases the tendency of a model to over-fit the data.
