Multiple grid electrode neuron transistor, manufacturing method therefor and formed nerve network

Abstract

The invention discloses a multiple grid electrode neuron transistor comprising source and drain electrodes, a channel, gate media, a floating gate electrode, a plurality of input grid electrodes and capacitance memory layers among the input grids and the gate media. All of the input grid electrodes and the gate media are jointly coupled onto the floating gate electrode via the capacitance memory layers, the channel is coordinately controlled to output a current, and a weighted computation function of neurons is simulated. The capacitance memory layers change in capacitance volume along with history of input grid voltage signals, and therefore plasticity of synaptic weight can be simulated. The invention also puts forward a manufacturing method for the multiple grid electrode neuron transistor and a nerve network which is formed via electric interconnection among a number of grid electrode neuron transistors. The multiple grid electrode neuron transistor is simple in structure and is convenient to manufacture and integrate, and the multiple grid electrode neuron transistor can hopefully be applied to the field of brain-like intelligent chips and the like.

Description

technical field [0001] The present invention relates to the field of semiconductor devices, in particular to a multi-gate neuron transistor, a preparation method thereof, and a formed neural network. Background technique [0002] The era of big data puts forward very high requirements for the ability of computers to process information, and the development of traditional von Neumann computers has encountered a bottleneck. Future computers need devices and chip architectures based on new instruction sets to meet the rapidly increasing information processing requirements in the era of big data. Compared with traditional von Neumann computers, the human brain stores and processes information in a distributed and parallel manner, which can better handle traditional "big data" problems such as perception, interaction, and recognition, and the overall energy consumption is very low. Low. Therefore, brain-like intelligence provides new ideas for the development of computer techno...

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Problems solved by technology

However, such a complex circuit scheme is not only cumbersome to prepare, but also has relatively high power consumption, which does not meet the low power consumption characteristics of the human brain.

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