In this work, we introduce a power efficient framework for approximated computations by taking advantage of the memristor-based multilayer neural networks. A ...

In this work, we introduce a power efficient framework for approximated computations by taking advantage of the memristor-based multilayer neural networks. A ...

(Memristor ACU) is introduced first to accelerate approximated computation and a memristor-based approximated computation framework with scalability is ...

In this work, we introduce a power efficient framework for approximated computations by taking advantage of the memristor-based multilayer neural networks. A ...

Aug 24, 2015 · In this work, we introduce a mixed-signal training acceleration framework, which realizes the self-training of memristor-based neural network.

In this work, we introduce a power efficient framework for approximated computations by taking advantage of the memristor-based multilayer neural networks. A ...

The core of HDC is to encode input samples into a hypervector, and then use it to query the class hypervector space. Compared with the conventional architecture ...

Oct 21, 2024 · Memristor-based In-Memory Computing is one of the ... memristors and the approximation of calculations or Approximate Computing (AxC).

By applying voltages at different input locations of this array and observing the output voltages, we can efficiently calculate matrix-vector products in the ...

This paper presents a general-purpose approximate computing paradigm for memristors and a memristor based hardware architecture, general-purpose field ...