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Memory

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DEW: A wavelet approach of rare sound event detection.

PloS one
This paper presents a novel sound event detection (SED) system for rare events occurring in an open environment. Wavelet multiresolution analysis (MRA) is used to decompose the input audio clip of 30 seconds into five levels. Wavelet denoising is the...

Promoting Personalized Reminiscence Among Cognitively Intact Older Adults Through an AI-Driven Interactive Multimodal Photo Album: Development and Usability Study.

JMIR aging
BACKGROUND: Reminiscence, a therapy that uses stimulating materials such as old photos and videos to stimulate long-term memory, can improve the emotional well-being and life satisfaction of older adults, including those who are cognitively intact. H...

Using deep neural networks to disentangle visual and semantic information in human perception and memory.

Nature human behaviour
Mental representations of familiar categories are composed of visual and semantic information. Disentangling the contributions of visual and semantic information in humans is challenging because they are intermixed in mental representations. Deep neu...

Heterogeneous Forgetting Rates and Greedy Allocation in Slot-Based Memory Networks Promotes Signal Retention.

Neural computation
A key question in the neuroscience of memory encoding pertains to the mechanisms by which afferent stimuli are allocated within memory networks. This issue is especially pronounced in the domain of working memory, where capacity is finite. Presumably...

A robust multi-scale feature extraction framework with dual memory module for multivariate time series anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Although existing reconstruction-based multivariate time series anomaly detection (MTSAD) methods have shown advanced performance, most assume the training data is clean. When faced with noise or contamination in training data, they can also reconstr...

SSTE: Syllable-Specific Temporal Encoding to FORCE-learn audio sequences with an associative memory approach.

Neural networks : the official journal of the International Neural Network Society
The circuitry and pathways in the brains of humans and other species have long inspired researchers and system designers to develop accurate and efficient systems capable of solving real-world problems and responding in real-time. We propose the Syll...

A sparse quantized hopfield network for online-continual memory.

Nature communications
An important difference between brains and deep neural networks is the way they learn. Nervous systems learn online where a stream of noisy data points are presented in a non-independent, identically distributed way. Further, synaptic plasticity in t...

Bio-inspired computational memory model of the Hippocampus: An approach to a neuromorphic spike-based Content-Addressable Memory.

Neural networks : the official journal of the International Neural Network Society
The brain has computational capabilities that surpass those of modern systems, being able to solve complex problems efficiently in a simple way. Neuromorphic engineering aims to mimic biology in order to develop new systems capable of incorporating s...

Operant Conditioning Neuromorphic Circuit With Addictiveness and Time Memory for Automatic Learning.

IEEE transactions on biomedical circuits and systems
Most operant conditioning circuits predominantly focus on simple feedback process, few studies consider the intricacies of feedback outcomes and the uncertainty of feedback time. This paper proposes a neuromorphic circuit based on operant conditionin...

Design and Implementation of Pavlovian Associative Memory Based on DNA Neurons.

IEEE transactions on neural networks and learning systems
In the field of biocomputing and neural networks, deoxyribonucleic acid (DNA) strand displacement (DSD) technology performs well in computation, programming, and information processing. In this article, the multiplication gate, addition gate, and thr...