Using the General Linear Model to Improve Performance in fNIRS Single Trial Analysis and Classification: A Perspective

Frontiers in Human Neuroscience - Switzerland
doi 10.3389/fnhum.2020.00030
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Frontiers Media SA

Related search

Pilot Study on Gait Classification Using fNIRS Signals

Computational Intelligence and Neuroscience
MedicineMathematicsComputer ScienceNeuroscience
2018English

Analysis of Growth Performance Data in Sheep Using Linear Mixed Model

World Journal of Agriculture and Soil Science
2019English

Improving Model-Based fNIRS Analysis Using Mesh-Based Anatomical and Light-Transport Models

2020English

Using Ensemble Technique to Improve Multiclass Classification

2019English

Using Argumentation to Improve Classification in Natural Language Problems

ACM Transactions on Internet Technology
Computer NetworksCommunications
2017English

A Linear Model Based on Kalman Filter for Improving Neural Network Classification Performance

Expert Systems with Applications
EngineeringComputer Science ApplicationsArtificial Intelligence
2016English

Two Solution Strategies to Improve the Computational Performance of Sequentially Linear Analysis for Quasi-Brittle Structures

International Journal for Numerical Methods in Engineering
Applied MathematicsNumerical AnalysisEngineering
2020English

Performance Analysis and Classification of the Ports in Gulf Countries Using Data Envelopment Analysis

American Journal of Transportation and Logistics
2019English

Testing for Spatial Heterogeneity in Functional MRI Using the Multivariate General Linear Model

IEEE Transactions on Medical Imaging
Electronic EngineeringUltrasound TechnologyRadiologicalComputer Science ApplicationsElectricalSoftware
2011English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy