AIMC Topic: Neural Networks, Computer

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Finite-time synchronization of uncertain coupled switched neural networks under asynchronous switching.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the finite-time synchronization problem for a class of uncertain coupled switched neural networks under asynchronous switching. By constructing appropriate Lyapunov-like functionals and using the average dwell time technique, so...

Role of Soft Computing Approaches in HealthCare Domain: A Mini Review.

Journal of medical systems
In the present era, soft computing approaches play a vital role in solving the different kinds of problems and provide promising solutions. Due to popularity of soft computing approaches, these approaches have also been applied in healthcare data for...

Decentralized event-triggered synchronization of uncertain Markovian jumping neutral-type neural networks with mixed delays.

Neural networks : the official journal of the International Neural Network Society
In this study, we present an approach for the decentralized event-triggered synchronization of Markovian jumping neutral-type neural networks with mixed delays. We present a method for designing decentralized event-triggered synchronization, which on...

A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy.

PloS one
This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted...

Synchronization of discrete-time neural networks with delays and Markov jump topologies based on tracker information.

Neural networks : the official journal of the International Neural Network Society
In this paper, synchronization in an array of discrete-time neural networks (DTNNs) with time-varying delays coupled by Markov jump topologies is considered. It is assumed that the switching information can be collected by a tracker with a certain pr...

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

BioMed research international
In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically ...

Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification.

Computational and mathematical methods in medicine
Recently, Deep Learning, especially through Convolutional Neural Networks (CNNs) has been widely used to enable the extraction of highly representative features. This is done among the network layers by filtering, selecting, and using these features ...

Concurrent study of stability and cytotoxicity of a novel nanoemulsion system - an artificial neural networks approach.

Pharmaceutical development and technology
Problems commonly associated with using nanoemulsions are their cytotoxic effects and low stability profiles. Here, for the first time, concentrations of ingredients of a nanoemulsion system were investigated to obtain the most stable nanoemulsion sy...

Stabilization of metastable dynamical rotating waves in a ring of unidirectionally coupled sigmoidal neurons due to shortcuts.

Neural networks : the official journal of the International Neural Network Society
Effects of shortcut connection on metastable dynamical rotating waves in a ring of sigmoidal neurons with unidirectional excitatory coupling are considered. A kinematical equation describing the propagation of wave fronts is derived with a sign funct...

A Flexible Approach for Human Activity Recognition Using Artificial Hydrocarbon Networks.

Sensors (Basel, Switzerland)
Physical activity recognition based on sensors is a growing area of interest given the great advances in wearable sensors. Applications in various domains are taking advantage of the ease of obtaining data to monitor personal activities and behavior ...