AIMC Topic: Discriminant Analysis

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Classification of cardiovascular tissues using LBP based descriptors and a cascade SVM.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Histological images have characteristics, such as texture, shape, colour and spatial structure, that permit the differentiation of each fundamental tissue and organ. Texture is one of the most discriminative features. The au...

Robust recursive absolute value inequalities discriminant analysis with sparseness.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a novel absolute value inequalities discriminant analysis (AVIDA) criterion for supervised dimensionality reduction. Compared with the conventional linear discriminant analysis (LDA), the main characteristics of our AVIDA ar...

Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.

eNeuro
Humans instantly recognize a previously seen face as "familiar." To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons w...

Resolving the effect of wrist position on myoelectric pattern recognition control.

Journal of neuroengineering and rehabilitation
BACKGROUND: The use of pattern recognition-based methods to control myoelectric upper-limb prostheses has been well studied in individuals with high-level amputations but few studies have demonstrated that it is suitable for partial-hand amputees, wh...

Towards Improved Design and Evaluation of Epileptic Seizure Predictors.

IEEE transactions on bio-medical engineering
OBJECTIVE: Key issues in the epilepsy seizure prediction research are (1) the reproducibility of results (2) the inability to compare multiple approaches directly. To overcome these problems, the seizure prediction challenge was organized on Kaggle.c...

Diagnostic value of sleep stage dissociation as visualized on a 2-dimensional sleep state space in human narcolepsy.

Journal of neuroscience methods
BACKGROUND: Type 1 narcolepsy (NT1) is characterized by symptoms believed to represent Rapid Eye Movement (REM) sleep stage dissociations, occurrences where features of wake and REM sleep are intermingled, resulting in a mixed state. We hypothesized ...

A Novel Graph Constructor for Semisupervised Discriminant Analysis: Combined Low-Rank and -Nearest Neighbor Graph.

Computational intelligence and neuroscience
Semisupervised Discriminant Analysis (SDA) is a semisupervised dimensionality reduction algorithm, which can easily resolve the out-of-sample problem. Relative works usually focus on the geometric relationships of data points, which are not obvious, ...

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

Journal of neural engineering
OBJECTIVE: Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a...

A ternary classification using machine learning methods of distinct estrogen receptor activities within a large collection of environmental chemicals.

The Science of the total environment
Endocrine-disrupting chemicals (EDCs), which can threaten ecological safety and be harmful to human beings, have been cause for wide concern. There is a high demand for efficient methodologies for evaluating potential EDCs in the environment. Herein ...

Robust differential expression analysis by learning discriminant boundary in multi-dimensional space of statistical attributes.

BMC bioinformatics
BACKGROUND: Performing statistical tests is an important step in analyzing genome-wide datasets for detecting genomic features differentially expressed between conditions. Each type of statistical test has its own advantages in characterizing certain...