English(EN) Neuromorphic Pseudo-Random Number Generators with a Low Power Hardware Implementation

神经形态PRNGs实现低功耗和高质量

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-30 21:10

研究人员开发了一种新颖的神经形态伪随机数生成器（NPRNG），它利用大脑高效生成不可预测序列的能力。这种新的NPRNG基于平衡脉冲神经网络模型，使用泄漏积分发放神经元，专为低功耗硬件实现而设计。在FPGA上实现的原型，在消耗仅3.24 mW的同时，以120kbps的速度展示了高质量的随机数生成。 AI

影响这项研究可能为AI和其他应用带来更高效、更低功耗的随机数生成。

排序理由该集群包含一篇学术论文，详细介绍了用于伪随机数生成的新计算模型和硬件实现。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.NE (Neural & Evolutionary) 阅读 →

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arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Wilten Nicola · 2026-09-30 21:10

具有低功耗硬件实现的神经形态伪随机数生成器

Pseudo-random number generation often requires trade-offs among quality, power consumption, and bandwidth to produce unpredictable sequences of numbers. The brain, on the other hand, efficiently generates unpredictable output complex network dynamics occurring in a high-dimension…

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具有低功耗硬件实现的神经形态伪随机数生成器

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