AIMC Topic: Algorithms

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Output-feedback adaptive neural control for stochastic nonlinear time-varying delay systems with unknown control directions.

IEEE transactions on neural networks and learning systems
This paper presents an adaptive output-feedback neural network (NN) control scheme for a class of stochastic nonlinear time-varying delay systems with unknown control directions. To make the controller design feasible, the unknown control coefficient...

Detection of temporal lobe epilepsy using support vector machines in multi-parametric quantitative MR imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The detection of MRI abnormalities that can be associated to seizures in the study of temporal lobe epilepsy (TLE) is a challenging task. In many cases, patients with a record of epileptic activity do not present any discernible MRI findings. In this...

Is extreme learning machine feasible? A theoretical assessment (part I).

IEEE transactions on neural networks and learning systems
An extreme learning machine (ELM) is a feedforward neural network (FNN) like learning system whose connections with output neurons are adjustable, while the connections with and within hidden neurons are randomly fixed. Numerous applications have dem...

Optimization of a multilayer neural network by using minimal redundancy maximal relevance-partial mutual information clustering with least square regression.

IEEE transactions on neural networks and learning systems
In this paper, an optimized multilayer feed-forward network (MLFN) is developed to construct a soft sensor for controlling naphtha dry point. To overcome the two main flaws in the structure and weight of MLFNs, which are trained by a back-propagation...

A two-layer recurrent neural network for nonsmooth convex optimization problems.

IEEE transactions on neural networks and learning systems
In this paper, a two-layer recurrent neural network is proposed to solve the nonsmooth convex optimization problem subject to convex inequality and linear equality constraints. Compared with existing neural network models, the proposed neural network...

Learning to track multiple targets.

IEEE transactions on neural networks and learning systems
Monocular multiple-object tracking is a fundamental yet under-addressed computer vision problem. In this paper, we propose a novel learning framework for tracking multiple objects by detection. First, instead of heuristically defining a tracking algo...

Kernel association for classification and prediction: a survey.

IEEE transactions on neural networks and learning systems
Kernel association (KA) in statistical pattern recognition used for classification and prediction have recently emerged in a machine learning and signal processing context. This survey outlines the latest trends and innovations of a kernel framework ...

Enhanced needle localization in ultrasound using beam steering and learning-based segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Segmentation of needles in ultrasound images remains a challenging problem. In this paper, we introduce a machine learning-based method for needle segmentation in 2D beam-steered ultrasound images. We used a statistical boosting approach to train a p...

A data-driven approach to prostate cancer detection from dynamic contrast enhanced MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Magnetic resonance imaging (MRI), particularly dynamic contrast enhanced (DCE) imaging, has shown great potential in prostate cancer diagnosis and staging. In the current practice of DCE-MRI, diagnosis is based on quantitative parameters extracted fr...

Alpha-plane based automatic general type-2 fuzzy clustering based on simulated annealing meta-heuristic algorithm for analyzing gene expression data.

Computers in biology and medicine
This paper considers microarray gene expression data clustering using a novel two stage meta-heuristic algorithm based on the concept of α-planes in general type-2 fuzzy sets. The main aim of this research is to present a powerful data clustering app...