AIMC Topic: Memory

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Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization.

Proceedings of the National Academy of Sciences of the United States of America Oct 12, 2018
Humans and most animals can learn new tasks without forgetting old ones. However, training artificial neural networks (ANNs) on new tasks typically causes them to forget previously learned tasks. This phenomenon is the result of "catastrophic forgett...
Neural Networks, Computer Task Performance and Analysis Memory Machine Learning Algorithms
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The stability of memristive multidirectional associative memory neural networks with time-varying delays in the leakage terms via sampled-data control.

PloS one Sep 24, 2018
In this paper, we propose a new model of memristive multidirectional associative memory neural networks, which concludes the time-varying delays in leakage terms via sampled-data control. We use the input delay method to turn the sampling system into...
Computer Simulation Neural Networks, Computer Time Factors Brain Mathematical Concepts Models, Neurological Humans Memory Nerve Net Association Systems Theory Models, Psychological
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Echo state networks are universal.

Neural networks : the official journal of the International Neural Network Society Sep 20, 2018
This paper shows that echo state networks are universal uniform approximants in the context of discrete-time fading memory filters with uniformly bounded inputs defined on negative infinite times. This result guarantees that any fading memory input/o...
Neural Networks, Computer Computer Systems Memory
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Sign backpropagation: An on-chip learning algorithm for analog RRAM neuromorphic computing systems.

Neural networks : the official journal of the International Neural Network Society Sep 1, 2018
Currently, powerful deep learning models usually require significant resources in the form of processors and memory, which leads to very high energy consumption. The emerging resistive random access memory (RRAM) has shown great potential for constru...
Memory Neural Networks, Computer Algorithms Deep Learning
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Monostable multivibrators as novel artificial neurons.

Neural networks : the official journal of the International Neural Network Society Aug 23, 2018
Retriggerable and non-retriggerable monostable multivibrators are simple timers with a single characteristic, their period. Motivated by the fact that monostable multivibrators are implementable in large quantities as counters in digital programmable...
Neural Networks, Computer Models, Neurological Neurons Memory
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Machine learning as a new paradigm for characterizing localization and lateralization of neuropsychological test data in temporal lobe epilepsy.

Epilepsy & behavior : E&B Aug 3, 2018
In this study, we employed a kernel support vector machine to predict epilepsy localization and lateralization for patients with a diagnosis of epilepsy (n = 228). We assessed the accuracy to which indices of verbal memory, visual memory, verbal flue...
Analysis of Variance Neuropsychological Tests Electroencephalography Epilepsy Memory Verbal Learning Adult Male Middle Aged Quality of Life Retrospective Studies Female Humans Machine Learning
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A Survey of Cognitive Architectures in the Past 20 Years.

IEEE transactions on cybernetics Aug 2, 2018
Building autonomous systems that achieve human level intelligence is one of the primary objectives in artificial intelligence (AI). It requires the study of a wide range of functions robustly across different phases of human cognition. This paper pre...
Humans Neural Networks, Computer Models, Neurological Artificial Intelligence Memory Cognition
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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 Jul 25, 2018
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...
Memory Speech Recognition Software Nanofibers Neural Networks, Computer
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Analysis and Simulation of Capacitor-Less ReRAM-Based Stochastic Neurons for the in-Memory Spiking Neural Network.

IEEE transactions on biomedical circuits and systems Jul 16, 2018
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 ...
Transistors, Electronic Memory Models, Neurological Neural Networks, Computer Poisson Distribution
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Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks.

Nature Jul 4, 2018
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...
Neural Networks, Computer Models, Neurological Pattern Recognition, Automated Memory DNA Neurons
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