Abstract

A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model.

Highlights

  • Memristor is a new circuit element postulated by Leon Chua in 1971 [1] and fabricated recently by the Stanley Williams group [2] from Hewlett-Packard (HP)

  • Circuit is a that constant value, the current through theindividual circuit is constant. It follows thatfunction the memristance. It follows the memristance variation of the memristor is a linear of pulse variation of the individual memristor is a linear function of pulse width since the memristance variation width since the memristance variation is a linear function of charge

  • Since composite memristance of the anti-serial circuit is a constant value, the current through the constant. It follows that the memristance variation of the individual memristor is a linear function of circuit is constant. It follows that the memristance variation of the individual memristor is a linear pulse width since the memristance variation is a linear function of charge

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Summary

Introduction

Memristor is a new circuit element postulated by Leon Chua in 1971 [1] and fabricated recently by the Stanley Williams group [2] from Hewlett-Packard (HP). Waser’s group reported a fabrication result of complementary resistive switch (CRS) consisting of two back-to-back (anti-serial) memristive elements for the construction of large passive crossbar arrays by 16, solving the sneak path problem [14]. We propose a linearized programming method utilizing an anti-serial. We propose a linearized programming method an memristor anti-serial architecture.

Memristor as a Promising Element for the Implementation of Neural Synapses
Inputs
Nonlinearity
Linearization in Memristor Programming with Anti-Serial Architecture
Memristor
D Roand ff
Simulation
V isof applied
Nonlinear ofthe the
13. Linearized
Conclusions
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