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Found 9 papers, 2 papers with code
Physical Principles for Scalable Neural Recording
Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience.
Neurons and Cognition Biological Physics
Neural Dust: An Ultrasonic, Low Power Solution for Chronic Brain-Machine Interfaces
A major hurdle in brain-machine interfaces (BMI) is the lack of an implantable neural interface system that remains viable for a lifetime.
Neurons and Cognition Instrumentation and Detectors
An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional Classifier
We present an end-to-end system combating this variability using a large-area, high-density sensor array and a robust classification algorithm.
Hyperdimensional Computing Nanosystem
By exploiting the unique properties of the underlying nanotechnologies, we show that HD computing, when implemented with monolithic 3D integration, can be up to 420X more energy-efficient while using 25X less area compared to traditional silicon CMOS implementations.
Analysis of Contraction Effort Level in EMG-Based Gesture Recognition Using Hyperdimensional Computing
Varying contraction levels of muscles is a big challenge in electromyography-based gesture recognition.
Vector Symbolic Architectures as a Computing Framework for Emerging Hardware
We see them acting as a framework for computing with distributed representations that can play a role of an abstraction layer for emerging computing hardware.
Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing
Machine learning algorithms deployed on edge devices must meet certain resource constraints and efficiency requirements.
Generalized Key-Value Memory to Flexibly Adjust Redundancy in Memory-Augmented Networks
Memory-augmented neural networks enhance a neural network with an external key-value memory whose complexity is typically dominated by the number of support vectors in the key memory.
Computing with Hypervectors for Efficient Speaker Identification
With only 1. 02k active parameters and a 128-minute pass through the training data we achieve Top-1 and Top-5 scores of 31% and 52% on the VoxCeleb1 dataset of 1, 251 speakers.
