AIMC Topic: Semiconductors

Clear Filters Showing 41 to 50 of 58 articles

Incoming Work-In-Progress Prediction in Semiconductor Fabrication Foundry Using Long Short-Term Memory.

Computational intelligence and neuroscience Jan 2, 2019
Preventive maintenance activities require a tool to be offline for long hour in order to perform the prescribed maintenance activities. Although preventive maintenance is crucial to ensure operational reliability and efficiency of the tool, long hour...
Reproducibility of Results Time Factors Semiconductors Neural Networks, Computer Machine Learning Forecasting
View on PubMed DOI

A 0.086-mm 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28-nm CMOS.

IEEE transactions on biomedical circuits and systems Nov 9, 2018
Shifting computing architectures from von Neumann to event-based spiking neural networks (SNNs) uncovers new opportunities for low-power processing of sensory data in applications such as vision or sensorimotor control. Exploring roads toward cogniti...
Semiconductors Probability Synapses Internet Neurons Neural Networks, Computer Time Factors Metals Neuronal Plasticity Action Potentials Oxides
View on PubMed DOI

QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments.

PloS one Oct 17, 2018
BACKGROUND: Over the past decade, machine learning techniques have revolutionized how research and science are done, from designing new materials and predicting their properties to data mining and analysis to assisting drug discovery to advancing cyb...
Data Mining Programming Languages Automation Computer Security Computational Biology Quantum Dots Semiconductors Reproducibility of Results Drug Discovery Neural Networks, Computer Machine Learning Algorithms Databases, Factual Computer Simulation
View on PubMed DOI

Handwritten-Digit Recognition by Hybrid Convolutional Neural Network based on HfO Memristive Spiking-Neuron.

Scientific reports Aug 22, 2018
Although there is a huge progress in complementary-metal-oxide-semiconductor (CMOS) technology, construction of an artificial neural network using CMOS technology to realize the functionality comparable with that of human cerebral cortex containing 1...
Humans Neural Networks, Computer Neurons Brain Semiconductors Handwriting Models, Neurological
View on PubMed DOI

Mimicking Biological Synaptic Functionality with an Indium Phosphide Synaptic Device on Silicon for Scalable Neuromorphic Computing.

ACS nano Jan 17, 2018
Neuromorphic or "brain-like" computation is a leading candidate for efficient, fault-tolerant processing of large-scale data as well as real-time sensing and transduction of complex multivariate systems and networks such as self-driving vehicles or I...
Synapses Silicon Crystallization Semiconductors Biomimetics Phosphines Biomimetic Materials Bionics Indium Neural Networks, Computer Equipment Design
View on PubMed DOI

Spiking Neural Classifier with Lumped Dendritic Nonlinearity and Binary Synapses: A Current Mode VLSI Implementation and Analysis.

Neural computation Dec 8, 2017
We present a neuromorphic current mode implementation of a spiking neural classifier with lumped square law dendritic nonlinearity. It has been shown previously in software simulations that such a system with binary synapses can be trained with struc...
Animals Metals Models, Neurological Action Potentials Oxides Semiconductors Neural Networks, Computer Dendrites Computers Pattern Recognition, Automated Nonlinear Dynamics Biomimetic Materials Electrical Equipment and Supplies Synapses
View on PubMed DOI

A Hybrid CMOS-Memristor Neuromorphic Synapse.

IEEE transactions on biomedical circuits and systems Dec 22, 2016
Although data processing technology continues to advance at an astonishing rate, computers with brain-like processing capabilities still elude us. It is envisioned that such computers may be achieved by the fusion of neuroscience and nano-electronics...
Synapses Semiconductors Electronics Animals Neural Networks, Computer Models, Neurological Neurons
View on PubMed DOI

Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting.

Sensors (Basel, Switzerland) Nov 2, 2016
A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS) image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care test...
Machine Learning Flow Cytometry Semiconductors Humans Blood Cell Count Microfluidic Analytical Techniques
View on PubMed DOI

Energy-Efficient Neuromorphic Classifiers.

Neural computation Aug 24, 2016
Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain....
Energy Metabolism Humans Neural Networks, Computer Support Vector Machine Semiconductors
View on PubMed DOI

All Spin Artificial Neural Networks Based on Compound Spintronic Synapse and Neuron.

IEEE transactions on biomedical circuits and systems May 17, 2016
Artificial synaptic devices implemented by emerging post-CMOS non-volatile memory technologies such as Resistive RAM (RRAM) have made great progress recently. However, it is still a big challenge to fabricate stable and controllable multilevel RRAM. ...
Memory Semiconductors Neural Networks, Computer Synapses Neurons Magnetics
View on PubMed DOI
Popular Topics
Recent Journals