Results 1 to 10 of about 31,264 (300)
Hyperdimensional decoding of spiking neural networks
This work presents a novel spiking neural network (SNN) decoding method, combining SNNs with hyperdimensional computing (HDC). This decoding method is designed to achieve high accuracy, high noise robustness, low inference latency and low energy ...
Cedrick Kinavuidi +2 more
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The more the merrier: running multiple neuromorphic components on-chip for robotic control
It has long been realized that neuromorphic hardware offers benefits for the domain of robotics such as low energy, low latency, as well as unique methods of learning.
Evan Eames +11 more
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Simulating brain-scale networks digitally is often hindered by extensive memory access. In this context, using low-precision data types and more efficient models to represent state variables is a viable alternative to improve the scalability of the ...
Pablo Urbizagastegui +2 more
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Biomechanical Modeling of Finger Joints Based on Dimeric Kinematics
In the literature, the proximal and distal interphalangeal joints (PIP and DIP) are usually described as singleaxis hinge joints, whereas the metacarpophalangeal (MCP) joint is typically described as a two-axis joint.
Franke Marc, Bogdan Martin
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In-memory computing facilitates efficient parallel computing based on the programmable memristor crossbar array. Proficient hardware image processing can be implemented by utilizing the analog vector-matrix operation with multiple memory states of the ...
Dong Yeon Woo +13 more
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Sequential analysis and its applications to neuromorphic engineering
Introduction:Neuromorphic circuits operate by comparing fluctuating signals to thresholds. This operation underpins sensing and computation in both neuromorphic architectures and biological nervous systems.
Shivaram Mani, Saeed Afshar, Travis Monk
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Scalable network emulation on analog neuromorphic hardware
We present a novel software feature for the BrainScaleS-2 accelerated neuromorphic platform that facilitates the partitioned emulation of large-scale spiking neural networks.
Elias Arnold +6 more
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Optical linear systems framework for event sensing and computational neuromorphic imaging
Event Vision Sensors, or neuromorphic cameras, report sparse, and asynchronous image change-related data and enable microsecond-scale sensing and high dynamic range, but challenge physics-based sensor design approaches.
Nimrod Kruger +4 more
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Zn2SnO4-Based Optoelectronic Synaptic Device for Visual Perception and Applications
Visual bionic systems are of crucial importance in the development of artificial intelligence for environmental perception. However, the traditional artificial vision system has problems such as complex system and high energy consumption due to the ...
Shan Xu +8 more
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Due to the increasing awareness of space security, encrypted space optic-communication has attracted significant attention. Consequently, ferroelectric memristors with efficient data processing capability and high operational stability become essential ...
Runyao Lin +9 more
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