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Memory

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Evaluation of the computational capabilities of a memristive random network (MN) under the context of reservoir computing.

Neural networks : the official journal of the International Neural Network Society
This work presents the simulation results of a novel recurrent, memristive neuromorphic architecture, the MN and explores its computational capabilities in the performance of a temporal pattern recognition task by considering the principles of the re...

Analysis and Simulation of Capacitor-Less ReRAM-Based Stochastic Neurons for the in-Memory Spiking Neural Network.

IEEE transactions on biomedical circuits and systems
The stochastic neuron is a key for event-based probabilistic neural networks. We propose a stochastic neuron using a metal-oxide resistive random-access memory (ReRAM). The ReRAM's conducting filament with built-in stochasticity is used to mimic the ...

Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks.

Nature
From bacteria following simple chemical gradients to the brain distinguishing complex odour information, the ability to recognize molecular patterns is essential for biological organisms. This type of information-processing function has been implemen...

Learning to activate logic rules for textual reasoning.

Neural networks : the official journal of the International Neural Network Society
Most current textual reasoning models cannotlearn human-like reasoning process, and thus lack interpretability and logical accuracy. To help address this issue, we propose a novel reasoning model which learns to activate logic rules explicitly via de...

Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

Neuron
The attractor neural network scenario is a popular scenario for memory storage in the association cortex, but there is still a large gap between models based on this scenario and experimental data. We study a recurrent network model in which both lea...

Runtime Programmable and Memory Bandwidth Optimized FPGA-Based Coprocessor for Deep Convolutional Neural Network.

IEEE transactions on neural networks and learning systems
The deep convolutional neural network (DCNN) is a class of machine learning algorithms based on feed-forward artificial neural network and is widely used for image processing applications. Implementation of DCNN in real-world problems needs high comp...

Spiking neural networks for handwritten digit recognition-Supervised learning and network optimization.

Neural networks : the official journal of the International Neural Network Society
We demonstrate supervised learning in Spiking Neural Networks (SNNs) for the problem of handwritten digit recognition using the spike triggered Normalized Approximate Descent (NormAD) algorithm. Our network that employs neurons operating at sparse bi...

GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework.

Neural networks : the official journal of the International Neural Network Society
Although deep neural networks (DNNs) are being a revolutionary power to open up the AI era, the notoriously huge hardware overhead has challenged their applications. Recently, several binary and ternary networks, in which the costly multiply-accumula...

Cognitive sequelae of endocrine therapy in women treated for breast cancer: a meta-analysis.

Breast cancer research and treatment
PURPOSE: Evidence suggests anti-estrogen endocrine therapy (ET) is associated with adverse cognitive effects; however, findings are based on small samples and vary in the cognitive abilities affected. We conducted a meta-analysis to quantitatively sy...

Exploring the Organization of Semantic Memory through Unsupervised Analysis of Event-related Potentials.

Journal of cognitive neuroscience
Modern multivariate methods have enabled the application of unsupervised techniques to analyze neurophysiological data without strict adherence to predefined experimental conditions. We demonstrate a multivariate method that leverages priming effects...