Fuzzy clustering of fMRI data: toward a theoretical basis for choosing the fuzziness index

2002 ◽  
Author(s):  
Martin Buerki ◽  
Helmut Oswald ◽  
Gerhard Schroth
Keyword(s):  
Fuzzy Clustering ◽  
Theoretical Basis ◽  
Fmri Data ◽  
Fuzziness Index

Bipolar Fuzzy Sets and Equilibrium Relations

2011 ◽  
pp. 129-158
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Clustering ◽  
Theoretical Basis ◽  
Cognitive Map ◽  
Global Regulation ◽  
Quantum Lattices ◽  
Bipolar Fuzzy Sets

Based on bipolar sets and quantum lattices, the concepts of bipolar fuzzy sets and equilibrium relations are presented in this chapter for bipolar fuzzy clustering, coordination, and global regulation. Related theorems are proved. Simulated application examples in multiagent macroeconomics are illustrated. Bipolar fuzzy sets and equilibrium relations provide a theoretical basis for cognitive-map-based bipolar decision, coordination, and global regulation.

Research on Reclassification of Power Users for TOU Power Price Based on Fuzzy Clustering

2012 ◽  
Vol 229-231 ◽  
pp. 1013-1016
Author(s):  
Ling Luo ◽  
Bao Chen Jiang ◽  
Li Kai Liang
Keyword(s):  
Power Consumption ◽  
Fuzzy Clustering ◽  
Theoretical Basis ◽  
Clustering Algorithm ◽  
Simulation Analysis ◽  
Reference Value ◽  
Actual Condition ◽  
Load Curve ◽  
Fuzzy Clustering Algorithm ◽  
Power Load

Study on TOU (Time-of-Use) power price in our country almost treats power users as a unified whole, but different categories of users have the different power consumption and way in the actual condition. Therefore, they have different responses to TOU power price. According to the power load features of all kinds of users, the paper presents a solution to reclassify the users using fuzzy clustering algorithm, and provides theoretical basis for implementing categorized TOU power price. Finally comparatively perfect effect is obtained by simulation analysis, and it has great reference value to perfect TOU power price and improve load curve.

scholarly journals Dissecting cognitive stages with time-resolved fMRI data: a comparison of fuzzy clustering and independent component analysis

2007 ◽  
Vol 25 (6) ◽  
pp. 860-868 ◽  
Author(s):  
Alain Smolders ◽  
Federico De Martino ◽  
Noël Staeren ◽  
Paul Scheunders ◽  
Jan Sijbers ◽  
...  
Keyword(s):  
Independent Component Analysis ◽  
Fuzzy Clustering ◽  
Component Analysis ◽  
Independent Component ◽  
Fmri Data ◽  
Time Resolved

scholarly journals Voxelwise encoding models with non-spherical multivariate normal priors

2018 ◽  
Author(s):  
Anwar O. Nunez-Elizalde ◽  
Alexander G. Huth ◽  
Jack L. Gallant
Keyword(s):  
Efficient Method ◽  
Predictive Models ◽  
Ridge Regression ◽  
Theoretical Basis ◽  
Expert Knowledge ◽  
Fmri Data ◽  
Model Parameters ◽  
Multivariate Normal ◽  
Computationally Efficient ◽  
Regression Methods

AbstractPredictive models for neural or fMRI data are often fit using regression methods that employ priors on the model parameters. One widely used method is ridge regression, which employs a spherical Gaussian prior that assumes equal and independent variance for all parameters. However, a spherical prior is not always optimal or appropriate. There are many cases where expert knowledge or hypotheses about the structure of the model parameters could be used to construct a better prior. In these cases, non-spherical Gaussian priors can be employed using a generalized form of ridge known as Tikhonov regression. Yet Tikhonov regression is only rarely used in neuroscience. In this paper we discuss the theoretical basis for Tikhonov regression, demonstrate a computationally efficient method for its application, and show several examples of how Tikhonov regression can improve predictive models for fMRI data. We also show that many earlier studies have implicitly used Tikhonov regression by linearly transforming the regressors before performing ridge regression.

Grey clustering model based on kernel and information field

2019 ◽  
Vol 10 (1) ◽  
pp. 56-67 ◽  
Author(s):  
Dang Luo ◽  
Zhang Huihui
Keyword(s):  
Weight Function ◽  
Fuzzy Clustering ◽  
Theoretical Basis ◽  
Disaster Risk ◽  
Content Type ◽  
Clustering Model ◽  
Grey Clustering ◽  
Drought Disaster ◽  
Regional Drought ◽  
Grey Number

Purpose The purpose of this paper is to propose a grey clustering model based on kernel and information field to deal with the situation in which both the observation values and the turning points of the whitenization weight function are interval grey numbers. Design/methodology/approach First, the “unreduced axiom of degree of greyness” was expanded to obtain the inference of “information field not-reducing”. Then, based on the theoretical basis of inference, the expression of whitenization weight function with interval grey number was provided. The grey clustering model and fuzzy clustering model were compared to analyse the relationship and difference between the two models. Finally, the paper model and the fuzzy clustering model were applied to the example analysis, and the interval grey number clustering model was established to analyse the influencing factors of regional drought disaster risk in Henan Province. Findings The example analysis results illustrate that although the two clustering methods have different theoretical basis, they are suitable for dealing with complex systems with uncertainty or grey characteristic, solving the problem of incomplete system information, which has certain feasibility and rationality. The clustering results of case study show that five influencing factors of regional drought disaster risk in Henan Province are divided into three classes, consistent with the actual situation, and they show the validity and practicability of the clustering model. Originality/value The paper proposes a new whitenization weight function with interval grey number that can transform interval grey number operations into real number operations. It not only simplifies the calculation steps, but it has a great significance for the “small data sets and poor information” grey system and has a universal applicability.

Video-Enhanced Microscopy--Better Visibility of Plant Cell Structures

1982 ◽  
Vol 40 ◽  
pp. 182-185
Author(s):  
N.S. Allen ◽  
R.D. Allen
Keyword(s):  
Diffraction Pattern ◽  
Theoretical Basis ◽  
Numerical Aperture ◽  
Gain Control ◽  
Control Unit ◽  
Camera Control ◽  
Variable Gain ◽  
Contrast Method ◽  
Fine Detail ◽  
Cell Structures

Various methods of video-enhanced microscopy combine TV cameras with light microscopes creating images with improved resolution, contrast and visibility of fine detail, which can be recorded rapidly and relatively inexpensively. The AVEC (Allen Video-enhanced Contrast) method avoids polarizing rectifiers, since the microscope is operated at retardations of λ/9- λ/4, where no anomaly is seen in the Airy diffraction pattern. The iris diaphram is opened fully to match the numerical aperture of the condenser to that of the objective. Under these conditions, no image can be realized either by eye or photographically. Yet the image becomes visible using the Hamamatsu C-1000-01 binary camera, if the camera control unit is equipped with variable gain control and an offset knob (which sets a clamp voltage of a D.C. restoration circuit). The theoretical basis for these improvements has been described.

Severe Paradoxical Dysphonia in Two Young Women

1993 ◽  
Vol 2 (3) ◽  
pp. 52-55 ◽  
Author(s):  
Michael Collins ◽  
Robert McDonald ◽  
Robert Stanley ◽  
Timothy Donovan ◽  
C. Frank Bonebrake
Keyword(s):  
Young Women ◽  
Theoretical Basis ◽  
Therapeutic Regimen ◽  
Instrumental Data ◽  
Relationship Of ◽  
The Relationship

This report describes an unusual and persistent dysphonia in two young women who had taken a therapeutic regimen of isotretinoin for intractable acne. We report perceptual and instrumental data for their dysphonia, and pose a theoretical basis for the relationship of dysphonia to this drug. We also provide recommendations for reducing the risk of acquiring a dysphonia during the course of treatment with isotretinoin.

Translation Research for the Rehabilitation of Left Spatial Neglect and Associated Disorders of Attention in Stroke Patients

2008 ◽  
Vol 18 (2) ◽  
pp. 55-65 ◽  
Author(s):  
Nkiruka Arene ◽  
Argye E. Hillis
Keyword(s):  
Theoretical Basis ◽  
Attention Bias ◽  
Spatial Neglect ◽  
Clinical Use ◽  
Stroke Patients ◽  
Translation Research ◽  
Unilateral Neglect ◽  
Assessment And Treatment ◽  
Sound Theoretical Basis ◽  
Review Current

Abstract The syndrome of unilateral neglect, typified by a lateralized attention bias and neglect of contralateral space, is an important cause of morbidity and disability after a stroke. In this review, we discuss the challenges that face researchers attempting to elucidate the mechanisms and effectiveness of rehabilitation treatments. The neglect syndrome is a heterogeneous disorder, and it is not clear which of its symptoms cause ongoing disability. We review current methods of neglect assessment and propose logical approaches to selecting treatments, while acknowledging that further study is still needed before some of these approaches can be translated into routine clinical use. We conclude with systems-level suggestions for hypothesis development that would hopefully form a sound theoretical basis for future approaches to the assessment and treatment of neglect.

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