Linear discriminant analysis (LDA) is one of the most popular classification algorithms for brain-computer interfaces (BCI). LDA assumes Gaussian distribution of the data, with equal covariance matrices for the concerned classes, however, the assumption is not usually held in actual BCI applications, where the heteroscedastic class distributions are usually observed. This paper proposes an enha...

Singularity problems of scatter matrices in Linear Discriminant Analysis (LDA) are challenging and have obtained attention during the last decade. Linear Discriminant Analysis via QR decomposition (LDA/QR) and Direct Linear Discriminant analysis (DLDA) are two popular algorithms to solve the singularity problem. This paper establishes the equivalent relationship between LDA/QR and DLDA. They ca...

The microscopic structure of a silicon vacancy is studied theoretically using first-principles supercell calculations. Both the standard Kohn–Sham local-density approximation (LDA) scheme and the generalized Kohn–Sham screened-exchange local-density approximation (sX-LDA) scheme are used. The latter approximation is expected to improve the description of electronic levels in the gap region subs...

Wear is the primary mechanism by which industrial plant deteriorates. By observing the amount and mechanism of wear periodically one is able to monitor the deterioration of plant. Traditionally this has been done by SOAP (spectrometric) analysis of used oil. In industrial drives this has a major deficiency, the most important size fraction, that is the particles above 10 microns are ignored. In...

Sophisticated big data machine learning applications are difficult to parallelize because it not only needs to process a big training dataset, it also needs to synchronize big model data in iterations. In parallel LDA, comparing synchronized and asynchronous communication methods under data parallelism and model parallelism, we note that the power-law distribution of word counts in LDA training...

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high ...

Linear Discriminant Analysis (LDA) is a well-known technique to improve the discrimination among classes or reduce the dimensionality with minimum loss of discrimination. It is generally used as a part of the front-end of speech recognizer with the classes defined on phone or subphone level. LDA with subphone-level classes (such as tied states or individual Gaussian densities) shows superior pe...

Copyright: 2014 The PLOS ONE Staff. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Figure 3. Topics learnxled by Red-LDA (top) and Vanilla LDA (bottom) on the EHR corpus. Both topics are about breast cancer (...

BACKGROUND Several lines of evidence suggest that male embryos may have greater vulnerability than female embryos to disordered inflammation; therefore, antiinflammatory drugs, such as low-dose aspirin (LDA), may alter the sex ratio. Here, we assessed the effect of LDA on male live birth and male offspring, incorporating pregnancy losses (n = 56) via genetic assessment, as part of a parallel-de...