matlab functions svmtrain (MathWorks Inc)
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matlab functions svmtrain
Matlab Functions Svmtrain, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/matlab+svmtrain+function/pm37239203-112-3-1
Average 90 stars, based on 1 article reviews
Matlab Functions Svmtrain, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/matlab+svmtrain+function/pm37239203-112-3-1
Average 90 stars, based on 1 article reviews
matlab functions svmtrain - by Bioz Stars,
2026-11
90/100 stars
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other:Article Title: Multiplexing working memory and time in the trajectories of neural networks. Article Snippet: Working memory (WM) and timing are generally considered distinct cognitive functions, but similar neural signatures have been implicated in both.. To explore the hypothesis that WM and timing may rely on shared neural mechanisms, we used psychophysical tasks that contained either task-irrelevant timing or WM components.. In both cases, the task-irrelevant component influenced performance. Article Title: Resting State Dynamic Reconfiguration of Spatial Attention Cortical Networks and Visuospatial Functioning in Non-Verbal Learning Disability (NVLD): A HD-EEG Investigation. Article Snippet: The Matlab functions svmtrain and svmclassify, respectively, were used in order to train a linear SVM model (with default parameters) for discriminating between the clinical and the control groups, starting from the functional connectivity matrices. Article Title: Human visual cortical gamma reflects natural image structure Article Snippet: Specifically, we used the Article Title: Multiplexing working memory and time: encoding retrospective and prospective information in neural trajectories Article Snippet: SVMs were trained (SVMTRAIN from Article Title: Study of cervical precancerous lesions detection by spectroscopy and support vector machine. Article Snippet: Background and objective: Diffuse reflectance spectroscopy (DRS) offers a fast, non-invasive, and low-cost alternative for cervical cancer diagnosis.. We aim to develop a method for screening precancerous lesions based on DRS. Material and methods: Characteristic parameters of cervical tissue were extracted from spectra, including optical characteristic parameters such as absorption and scattering coefficients, and some slope and area parameters of the spectrum.. Data were randomly divided into training (60%) and test (40%) sets. Extraction:Article Title: Corticomuscular Co-Activation Based Hybrid Brain-Computer Interface for Motor Recovery Monitoring Article Snippet: .. The feature extraction function is developed in-house while we have used the MATLAB’s |