⚡ 本页包含 AI 生成的分析内容，仅供参考
提出一种57mW嵌入式混合模式神经模糊加速器，集成于智能多核处理器中，用于解决传统软件实现神经网络和模糊系统在功耗与速度上的瓶颈。
portable game consoles, and robots for such intelligent applications as object detection, recognition, and human-computer interfaces (HCI). Most of these functions are realized in software with neural networks (NN) and fuzzy systems (FS), but due to power and speed limitations, a hardware solution is needed. For example, software implementations of object-recognition algorithms like SIFT consume ~10W and ~1s delay even on a 2.4GHz PC CPU. Previously, GPGPUs or ASICs were used to realize AI functions [1-2]. But GPGPUs just emulate NN/FS with many processing elements to speed up the software, while still consuming a large amount of power. On the other hand, low-power ASICs have been mostly dedicated stand-alone processors, not suitable to be ported into many different systems [2]. This paper presents a portable embedded neuro-fuzzy accelerator: the intelligent
Jinwook Oh, Junyoung Park, Gyeonghoon Kim, Seungjin Lee, Hoi-Jun Yoo
KAIST, Daejeon, Korea Artificial intelligence (AI) functions are becoming important in smartphones,