AIMC Topic: Neural Networks, Computer

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Learning to Select Supplier Portfolios for Service Supply Chain.

PloS one
The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier p...

Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets.

IEEE transactions on biomedical circuits and systems
Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking the neuro...

Developing Artificial Neural Network Models to Predict Functioning One Year After Traumatic Spinal Cord Injury.

Archives of physical medicine and rehabilitation
OBJECTIVE: To develop mathematical models for predicting level of independence with specific functional outcomes 1 year after discharge from inpatient rehabilitation for spinal cord injury.

Synchronization of fractional-order complex-valued neural networks with time delay.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the problem of synchronization of fractional-order complex-valued neural networks with time delays. By means of linear delay feedback control and a fractional-order inequality, sufficient conditions are obtained to guarantee the...

Mapping Generative Models onto a Network of Digital Spiking Neurons.

IEEE transactions on biomedical circuits and systems
Stochastic neural networks such as Restricted Boltzmann Machines (RBMs) have been successfully used in applications ranging from speech recognition to image classification, and are particularly interesting because of their potential for generative ta...

Financial Time Series Prediction Using Elman Recurrent Random Neural Networks.

Computational intelligence and neuroscience
In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed an architecture which combined Elman recurrent neural networks with stochastic time effective fu...

Course Control of Underactuated Ship Based on Nonlinear Robust Neural Network Backstepping Method.

Computational intelligence and neuroscience
The problem of course control for underactuated surface ship is addressed in this paper. Firstly, neural networks are adopted to determine the parameters of the unknown part of ideal virtual backstepping control, even the weight values of neural netw...

Accelerating Convolutional Sparse Coding for Curvilinear Structures Segmentation by Refining SCIRD-TS Filter Banks.

IEEE transactions on medical imaging
Deep learning has shown great potential for curvilinear structure (e.g., retinal blood vessels and neurites) segmentation as demonstrated by a recent auto-context regression architecture based on filter banks learned by convolutional sparse coding. H...

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

IEEE transactions on biomedical circuits and systems
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. ...

Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil.

PloS one
Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approa...