AIMC Topic: Algorithms

Clear Filters Showing 23431 to 23440 of 28713 articles

Stochastic sampled-data control for synchronization of complex dynamical networks with control packet loss and additive time-varying delays.

Neural networks : the official journal of the International Neural Network Society
This study examines the exponential synchronization of complex dynamical networks with control packet loss and additive time-varying delays. Additionally, sampled-data controller with time-varying sampling period is considered and is assumed to switc...

RSTFC: A Novel Algorithm for Spatio-Temporal Filtering and Classification of Single-Trial EEG.

IEEE transactions on neural networks and learning systems
Learning optimal spatio-temporal filters is a key to feature extraction for single-trial electroencephalogram (EEG) classification. The challenges are controlling the complexity of the learning algorithm so as to alleviate the curse of dimensionality...

Bidirectional Active Learning: A Two-Way Exploration Into Unlabeled and Labeled Data Set.

IEEE transactions on neural networks and learning systems
In practical machine learning applications, human instruction is indispensable for model construction. To utilize the precious labeling effort effectively, active learning queries the user with selective sampling in an interactive way. Traditional ac...

An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction.

IEEE transactions on neural networks and learning systems
We consider the task of performing prediction with neural networks (NNs) on the basis of uncertain input data expressed in the form of intervals. We aim at quantifying the uncertainty in the prediction arising from both the input data and the predict...

Artificial neuron-glia networks learning approach based on cooperative coevolution.

International journal of neural systems
Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and...

Multiple actor-critic structures for continuous-time optimal control using input-output data.

IEEE transactions on neural networks and learning systems
In industrial process control, there may be multiple performance objectives, depending on salient features of the input-output data. Aiming at this situation, this paper proposes multiple actor-critic structures to obtain the optimal control via inpu...

Application of a hybrid method combining grey model and back propagation artificial neural networks to forecast hepatitis B in china.

Computational and mathematical methods in medicine
Accurate incidence forecasting of infectious disease provides potentially valuable insights in its own right. It is critical for early prevention and may contribute to health services management and syndrome surveillance. This study investigates the ...

L1-norm locally linear representation regularization multi-source adaptation learning.

Neural networks : the official journal of the International Neural Network Society
In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the larg...

Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also ...

Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning.

Translational psychiatry
Although the prevalence of autism spectrum disorder (ASD) has risen sharply in the last few years reaching 1 in 68, the average age of diagnosis in the United States remains close to 4--well past the developmental window when early intervention has t...