tightened, or reduced • Go to the appropriate table to find sample size and pass/fail numbers Effectiveness of Sample Testing • Very bad batches will most likely be rejected • Good batches will most likely be accepted • Marginally unacceptable batches are ...
Error in sampling can be reduced by increasing the sample size. Bias is more elusive. It cannot be measured. We can only minimize it via a well-planned and well-executed design plan.doi:10.1080/01621459.1923.10502129Burton H. CampTaylor & Francis GroupPublications of the American Statistical ...
The offset voltage generated between an input signal VS applied to a signal input terminal 2 and an output signal VO applied to the signal output terminal 3 can be reduced by adjusting said I1, I2, i.e., currents flowing into the diodes D1, D2. 展开 ...
Finally, the character limits of SMS messaging, and the desire to limit the amount of information in WhatsApp invitations, meant that we could not provide participants with as much information in mobile invitations as we could in an email which may have reduced potential participants’ willingness...
For "basic" DBPSK (i.e., using rectangular pulseshape), the error floor can be eliminated completely, but has finite values for pulses with raised-cosine spectrum. For a/4 DQPSK, the error floor is reduced by only a factor on the order of two as compared to fixed sampling...
For signals with sparse /spl Fscr/, this rate can be much smaller than the Nyquist rate. Unfortunately the reduced sampling rates afforded by this scheme can be accompanied by increased error sensitivity. In a previous study, we derived bounds on the error due to mismodeling and sample ...
Flood susceptibility modelling using novel hybrid approach of reduced-error pruning trees with bagging and random subspace ensembles J. Hydrol., 575 (2019), pp. 864-873 View PDFView articleView in ScopusGoogle Scholar Chen et al., 2018 W. Chen, H. Shahabi, S. Zhang, K. Khosravi, A. Shi...
Generated examples can be reduced by using only a subset of the initial dataset \({{{\mathcal{D}}}\) as seeds. Even then, the optimization of δ may lead to structures which are very similar, corresponding to the same points in the configuration space. To avoid evaluating the same geome...
The prevalence of sampling errors can be reduced by increasing the sample size. In general, sampling errors can be placed into four categories: population-specific error, selection error, sample frame error, or non-response error. Understanding Sampling Errors A sampling error is a deviation in th...
respectively.It can be concluded that the error of a certain algorithm by non-uniform sampling is lower than by uniform sampling method;when the sampling number is 250,FBG peak error of Gaussian fitting algorithm under non-uniform sampling method is reduced by 38.46% than uniform sampling method...