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Hidden Bursting Firings and Bifurcation Mechanisms in Memristive Neuron Model With Threshold Electromagnetic Induction.
IEEE transactions on neural networks and learning systems
Apr 11, 2019
Memristors can be employed to mimic biological neural synapses or to describe electromagnetic induction effects. To exhibit the threshold effect of electromagnetic induction, this paper presents a threshold flux-controlled memristor and examines its ...
Information Transmitted From Bioinspired Neuron-Astrocyte Network Improves Cortical Spiking Network's Pattern Recognition Performance.
IEEE transactions on neural networks and learning systems
Apr 11, 2019
We trained two spiking neural networks (SNNs), the cortical spiking network (CSN) and the cortical neuron-astrocyte network (CNAN), using a spike-based unsupervised method, on the MNIST and alpha-digit data sets and achieve an accuracy of 96.1% and 7...
ML-DSP: Machine Learning with Digital Signal Processing for ultrafast, accurate, and scalable genome classification at all taxonomic levels.
BMC genomics
Apr 3, 2019
BACKGROUND: Although software tools abound for the comparison, analysis, identification, and classification of genomic sequences, taxonomic classification remains challenging due to the magnitude of the datasets and the intrinsic problems associated ...
Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things.
Sensors (Basel, Switzerland)
Apr 2, 2019
Multi-agent hybrid social cognitive optimization (MAHSCO) based on the Internet of Things (IoT) is suggested to solve the problem of the generation of formations of unmanned vehicles. Through the analysis of the unmanned vehicle formation problem, fo...
Bagging and deep learning in optimal individualized treatment rules.
Biometrics
Mar 29, 2019
An ENsemble Deep Learning Optimal Treatment (EndLot) approach is proposed for personalized medicine problems. The statistical framework of the proposed method is based on the outcome weighted learning (OWL) framework which transforms the optimal deci...
Learning mechanisms in cue reweighting.
Cognition
Mar 28, 2019
Feedback has been shown to be effective in shifting attention across perceptual cues to a phonological contrast in speech perception (Francis, Baldwin & Nusbaum, 2000). However, the learning mechanisms behind this process remain obscure. We compare t...
Smeared multiscale finite element model for electrophysiology and ionic transport in biological tissue.
Computers in biology and medicine
Mar 26, 2019
Basic functions of living organisms are governed by the nervous system through bidirectional signals transmitted from the brain to neural networks. These signals are similar to electrical waves. In electrophysiology the goal is to study the electrica...
Appetite ratings of foods are predictable with an in vitro advanced gastrointestinal model in combination with an in silico artificial neural network.
Food research international (Ottawa, Ont.)
Mar 25, 2019
The expected increase of global obesity prevalence makes it necessary to have information about the effects of meal intakes on the feeling of appetite. Because human clinical studies are time and cost intensive, there is a need for a reliable alterna...
Autonomous Molecular Design: Then and Now.
ACS applied materials & interfaces
Mar 25, 2019
The success of deep machine learning in processing of large amounts of data, for example, in image or voice recognition and generation, raises the possibilities that these tools can also be applied for solving complex problems in materials science. I...
A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis.
Computational and mathematical methods in medicine
Mar 25, 2019
This study reviews the technique of convolutional neural network (CNN) applied in a specific field of mammographic breast cancer diagnosis (MBCD). It aims to provide several clues on how to use CNN for related tasks. MBCD is a long-standing problem, ...
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