AIMC Topic: Neural Networks, Computer

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A Highly Effective and Robust Membrane Potential-Driven Supervised Learning Method for Spiking Neurons.

IEEE transactions on neural networks and learning systems
Spiking neurons are becoming increasingly popular owing to their biological plausibility and promising computational properties. Unlike traditional rate-based neural models, spiking neurons encode information in the temporal patterns of the transmitt...

Delayed state-feedback control for stabilization of neural networks with leakage delay.

Neural networks : the official journal of the International Neural Network Society
This paper mainly deals with the problem of designing delayed state-feedback controller for neural networks with leakage delay. By constructing an appropriate Lyapunov-Krasovskii functional including double integral terms having two different exponen...

MfeCNN: Mixture Feature Embedding Convolutional Neural Network for Data Mapping.

IEEE transactions on nanobioscience
Data mapping plays an important role in data integration and exchanges among institutions and organizations with different data standards. However, traditional rule-based approaches and machine learning methods fail to achieve satisfactory results fo...

Adaptive critic designs for optimal control of uncertain nonlinear systems with unmatched interconnections.

Neural networks : the official journal of the International Neural Network Society
In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying a...

Affinity network fusion and semi-supervised learning for cancer patient clustering.

Methods (San Diego, Calif.)
Defining subtypes of complex diseases such as cancer and stratifying patient groups with the same disease but different subtypes for targeted treatments is important for personalized and precision medicine. Approaches that incorporate multi-omic data...

Epileptic seizure anticipation and localisation of epileptogenic region using EEG signals.

Journal of medical engineering & technology
Electric activity of brain gets disturbed prior to epileptic seizure onset. Early prediction of an upcoming seizure can help to increase effectiveness of antiepileptic drugs. The scalp electroencephalogram signals contain information about the dynami...

Design, verification and robotic application of a novel recurrent neural network for computing dynamic Sylvester equation.

Neural networks : the official journal of the International Neural Network Society
To solve dynamic Sylvester equation in the presence of additive noises, a novel recurrent neural network (NRNN) with finite-time convergence and excellent robustness is proposed and analyzed in this paper. As compared with the design process of Zhang...

An On-Chip Trainable and the Clock-Less Spiking Neural Network With 1R Memristive Synapses.

IEEE transactions on biomedical circuits and systems
Spiking neural networks (SNNs) are being explored in an attempt to mimic brain's capability to learn and recognize at low power. Crossbar architecture with highly scalable resistive RAM or RRAM array serving as synaptic weights and neuronal drivers i...

Microaneurysm Detection Using Principal Component Analysis and Machine Learning Methods.

IEEE transactions on nanobioscience
Diabetic retinopathy (DR) is an eye abnormality caused by long-term diabetes and it is the most common cause of blindness before the age of 50. Microaneurysms (MAs), resulting from leakage from retinal blood vessels, are early indicators of DR. In th...