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Neural network synapse structure based on memristive devices and synaptic weight building method

A technology of memristive device and neural network, applied in the field of synaptic structure of neural network, can solve the problem that conductance cannot be negative, etc.

Active Publication Date: 2015-09-16
LYNXI TECH CO LTD
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  • Abstract
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Problems solved by technology

Since memristive devices use conductance as an independent variable, and conductance cannot be negative, this type of synaptic structure can only achieve one-way weighting

Method used

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  • Neural network synapse structure based on memristive devices and synaptic weight building method
  • Neural network synapse structure based on memristive devices and synaptic weight building method
  • Neural network synapse structure based on memristive devices and synaptic weight building method

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Embodiment Construction

[0015] The memristive device-based neural network synapse structure provided by the present invention will be further described in detail below in conjunction with the drawings and specific embodiments.

[0016] See figure 2 , which is a memristive device-based neural network synapse structure 10 provided by the present invention, including: a first memristive device G1, a second memristive device G2, a voltage inverter T, an operational amplifier A, and a feedback resistor Rf. The input terminal of the first memristive device G1 and the input voltage directly connected, the input terminal of the second memristive device G2 is connected to the input voltage through the voltage inverter T connected, the output end of the first memristive device G1 and the output end of the second memristive device G2 are respectively connected to the inverting input end of the operational amplifier A, and the same input end of the operational amplifier A is grounded, The feedback resistor ...

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Abstract

The invention provides a neural network synapse structure based on memristive devices. The neural network synapse structure comprises a first memristive device, a second memristive device, a voltage inverter, an operational amplifier and a feedback resistor, wherein the second memristive device is serially connected with the voltage inverter to form a serial connection structure, and the serial connection structure is in parallel connection with the first memristive device to form a parallel connection structure; and one end of the parallel connection structure is connected with an input voltage, and the other end of the parallel connection structure is connected with the reverse input end of the operational amplifier and the feedback resistor is bridged between the output end and the reverse input end of the operational amplifier.

Description

technical field [0001] The invention relates to a neural network synapse structure, in particular to a neural network synaptic structure based on a memristive device. Background technique [0002] Synapses are key primitives in neural networks, and modifying synaptic weights according to certain algorithms is the basis of information processing in neural networks. The synaptic weights of neural networks usually have two types of excitatory and inhibitory, that is, positive weights and negative weights. A memristive device is a plastic electronic device whose conductance value can be adjusted by an applied electrical signal. Its good plasticity, small size, low energy consumption, and high reading and writing speed make it a synaptic device in future neuromorphic engineering. best choice. However, the synaptic structure based on memristive devices in the prior art cannot fully realize the bidirectional weights of neural networks. For example, figure 1 A synaptic structure...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G11C13/00H03K19/00
Inventor 施路平邓磊裴京李国齐王栋
Owner LYNXI TECH CO LTD
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