AIMC Topic: Algorithms

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Epileptic Focus Localization Using Discrete Wavelet Transform Based on Interictal Intracranial EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Over the past decade, with the development of machine learning, discrete wavelet transform (DWT) has been widely used in computer-aided epileptic electroencephalography (EEG) signal analysis as a powerful time-frequency tool. But some important probl...

Unsupervised class labeling of diffuse lung diseases using frequent attribute patterns.

International journal of computer assisted radiology and surgery
PURPOSE: For realizing computer-aided diagnosis (CAD) of computed tomography (CT) images, many pattern recognition methods have been applied to automatic classification of normal and abnormal opacities; however, for the learning of accurate classifie...

H state estimation for memristive neural networks with time-varying delays: The discrete-time case.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the H state estimation problem for a class of discrete-time memristive neural networks (DMNNs) with time-varying delays. For the sake of coping with the switched weight matrices, the DMNNs are recast into a tractable model by ...

Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning.

Neural networks : the official journal of the International Neural Network Society
Most of machine learning approaches have stemmed from the application of minimizing the mean squared distance principle, based on the computationally efficient quadratic optimization methods. However, when faced with high-dimensional and noisy data, ...

An Efficient Data Partitioning to Improve Classification Performance While Keeping Parameters Interpretable.

PloS one
Supervised machine learning methods typically require splitting data into multiple chunks for training, validating, and finally testing classifiers. For finding the best parameters of a classifier, training and validation are usually carried out with...

Semi-supervised learning for ordinal Kernel Discriminant Analysis.

Neural networks : the official journal of the International Neural Network Society
Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels...

A Novel Flexible Inertia Weight Particle Swarm Optimization Algorithm.

PloS one
Particle swarm optimization (PSO) is an evolutionary computing method based on intelligent collective behavior of some animals. It is easy to implement and there are few parameters to adjust. The performance of PSO algorithm depends greatly on the ap...

Purely Structural Protein Scoring Functions Using Support Vector Machine and Ensemble Learning.

IEEE/ACM transactions on computational biology and bioinformatics
The function of a protein is determined by its structure, which creates a need for efficient methods of protein structure determination to advance scientific and medical research. Because current experimental structure determination methods carry a h...

Mean-square exponential input-to-state stability of delayed Cohen-Grossberg neural networks with Markovian switching based on vector Lyapunov functions.

Neural networks : the official journal of the International Neural Network Society
This paper studies the mean-square exponential input-to-state stability of delayed Cohen-Grossberg neural networks with Markovian switching. By using the vector Lyapunov function and property of M-matrix, two generalized Halanay inequalities are esta...

Using the Generalized Index of Dissimilarity to Detect Gene-Gene Interactions in Multi-Class Phenotypes.

PloS one
To find genetic association between complex diseases and phenotypic traits, one important procedure is conducting a joint analysis. Multifactor dimensionality reduction (MDR) is an efficient method of examining the interactions between genes in genet...