نتایج جستجو برای: u lda
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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 effects of magnetism on high pressure properties of transition metals and transition metal compounds can be quite important. In the case of Fe, magnetism is responsible for stability of the body-centered cubic (bcc) phase at ambient conditions, and the large thermal expansivity in face-centered cubic (fcc) iron, and also has large effects on the equation of state and elasticity of hexagon...
The optical properties of ZnO nanowires containing defects are investigated using first-principles densityfunctional theory incorporating the LDA+U formalism. Calculations include defects in the form of substitutional N, Zn, and O vacancies as well as +1 charged O vacancy. Our calculations reveal that the presence of vacancies contribute strongly to optical absorption in the visible. Furthermor...
A comparative analysis of the electronic structure obtained in DFT/LDA and LDA + DMFT approaches possible isostructural analogues iron superconductors InCo 2 As KInCo 4 with parent high-temperature superconductor system BaFe is carried out. It established that spite rather large value electron-electron correlations (local Coulomb interaction on Co- $$3d$$ shell $$U = 4.0$$ eV, Hund exchange $$J...
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 (...
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