Hardware Option

14,000,000 Leading Edge Experts on the ideXlab platform

Scan Science and Technology

Contact Leading Edge Experts & Companies

Scan Science and Technology

Contact Leading Edge Experts & Companies

The Experts below are selected from a list of 7410 Experts worldwide ranked by ideXlab platform

Young I. A. - One of the best experts on this subject based on the ideXlab platform.

  • Convolution Inference via Synchronization of a Coupled CMOS Oscillator Array
    2019
    Co-Authors: Nikonov D. E., Kurahashi P., Ayers J. S., Lee H. -j., Fan Y., Young I. A.
    Abstract:

    Oscillator neural networks (ONN) are a promising Hardware Option for artificial intelligence. With an abundance of theoretical treatments of ONNs, few experimental implementations exist to date. In contrast to prior publications of only building block functionality, we report a practical experimental demonstration of neural computing using an ONN. The arrays contain 26 CMOS ring oscillators in the GHz range of frequencies tuned by image data and filters. Synchronization of oscillators results in an analog output voltage approximating convolution neural network operation.Comment: 4 pages, 11 figure

Nikonov D. E. - One of the best experts on this subject based on the ideXlab platform.

  • Convolution Inference via Synchronization of a Coupled CMOS Oscillator Array
    2019
    Co-Authors: Nikonov D. E., Kurahashi P., Ayers J. S., Lee H. -j., Fan Y., Young I. A.
    Abstract:

    Oscillator neural networks (ONN) are a promising Hardware Option for artificial intelligence. With an abundance of theoretical treatments of ONNs, few experimental implementations exist to date. In contrast to prior publications of only building block functionality, we report a practical experimental demonstration of neural computing using an ONN. The arrays contain 26 CMOS ring oscillators in the GHz range of frequencies tuned by image data and filters. Synchronization of oscillators results in an analog output voltage approximating convolution neural network operation.Comment: 4 pages, 11 figure

Kurahashi P. - One of the best experts on this subject based on the ideXlab platform.

  • Convolution Inference via Synchronization of a Coupled CMOS Oscillator Array
    2019
    Co-Authors: Nikonov D. E., Kurahashi P., Ayers J. S., Lee H. -j., Fan Y., Young I. A.
    Abstract:

    Oscillator neural networks (ONN) are a promising Hardware Option for artificial intelligence. With an abundance of theoretical treatments of ONNs, few experimental implementations exist to date. In contrast to prior publications of only building block functionality, we report a practical experimental demonstration of neural computing using an ONN. The arrays contain 26 CMOS ring oscillators in the GHz range of frequencies tuned by image data and filters. Synchronization of oscillators results in an analog output voltage approximating convolution neural network operation.Comment: 4 pages, 11 figure

Ayers J. S. - One of the best experts on this subject based on the ideXlab platform.

  • Convolution Inference via Synchronization of a Coupled CMOS Oscillator Array
    2019
    Co-Authors: Nikonov D. E., Kurahashi P., Ayers J. S., Lee H. -j., Fan Y., Young I. A.
    Abstract:

    Oscillator neural networks (ONN) are a promising Hardware Option for artificial intelligence. With an abundance of theoretical treatments of ONNs, few experimental implementations exist to date. In contrast to prior publications of only building block functionality, we report a practical experimental demonstration of neural computing using an ONN. The arrays contain 26 CMOS ring oscillators in the GHz range of frequencies tuned by image data and filters. Synchronization of oscillators results in an analog output voltage approximating convolution neural network operation.Comment: 4 pages, 11 figure

Lee H. -j. - One of the best experts on this subject based on the ideXlab platform.

  • Convolution Inference via Synchronization of a Coupled CMOS Oscillator Array
    2019
    Co-Authors: Nikonov D. E., Kurahashi P., Ayers J. S., Lee H. -j., Fan Y., Young I. A.
    Abstract:

    Oscillator neural networks (ONN) are a promising Hardware Option for artificial intelligence. With an abundance of theoretical treatments of ONNs, few experimental implementations exist to date. In contrast to prior publications of only building block functionality, we report a practical experimental demonstration of neural computing using an ONN. The arrays contain 26 CMOS ring oscillators in the GHz range of frequencies tuned by image data and filters. Synchronization of oscillators results in an analog output voltage approximating convolution neural network operation.Comment: 4 pages, 11 figure

Hardware Option - 15 days free trial to Access Experts & Abstracts