Capacitor-Less Low-Power Neuron Circuit with Multi-Gate Feedback Field Effect Transistor
Round 1
Reviewer 1 Report
In the paper, author propose a low-power neuron circuit with a multi-gate feedback field effect transistor (FBFET) that can perform integration without a capacitor to solve the problem of an analog neuron circuit. The paper is innovative. However, the paper can be published after following revisions:
（1） There is too little theoretical analysis in the paper. Authors may theoretically analyze input-output relationship of multi-gate feedback field effect transistor and low power neuron circuit, gate capacitance of multi-gate feedback field effect transistor, power consumption of neuron circuit, and so on.
（2） The introduction of the paper is too simple. It should start with the application of neurons, then the implementation of neurons, and then the proposed Multi-gate Feedback Field Effect Transistor neurons. The references in the introduction are a little thin. For applications in neurons, the following applications and references can be added：1) Associative memory：[1]Memristor-based affective associative memory neural network circuit with emotional gradual processes, Neural Computing & Applications, 2022, 2022,34(16):13667-13682; [2]A Memristive Spiking Neural Network Circuit with Selective Supervised Attention Algorithm, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022, DOI: 10.1109/TCAD.2022.3228896. 2）The generation of chaotic signals: [3]A Memristive Synapse Control Method to Generate Diversified Multi-Structure Chaotic Attractors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022, DOI: 10.1109/TCAD.2022.3186516. 3）information security: [4]Observer-based synchronization of memristive neural networks under DoS attacks and actuator saturation and its application to image encryption, Applied Mathematics and Computation, 2022, 425: 127080
（3） In the paper, to verify the low power neuron circuit, authors may increase an example of application of low power neuron circuit based on multi-gate feedback field effect transistor.
Author Response
Dear reviewer 1
I attached the file. Thank you for your feedback
Author Response File: 
Author Response.docx
Reviewer 2 Report
The authors presented work on neuron circuit based on multi-gate Feedback FET. The authors have resented some interesting results. I would recommend the work given that the authors must clarify a few concerns. The introduction is quite short and lacks many latest references as the work on neurons with different devices is already published. Use the subscript and superscript wherever necessary and use "V" to represent the volt unit (not "v"). Which TCAD tool is used to simulate the device? Are the used analytical models or the device results experimentally calibrated? Kindly mention or explain the used code in the supplementary information for the readers to replicate the possible work. Is the numerical analysis of the device transient or quasi-static? Why does the current for Vds=0.8V increase and then saturate with a 3-order variation? Kindly add the spice code used to simulate the circuit in the supplementary material. What are the characteristics of the p-FET used as pull-up transistor? Which FETs are used to design the inverter?
Author Response
Dear reviewer 2
I attached the file. Thank you for your feedback
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
The revised paper has addressed my questions, it can be published.
Reviewer 2 Report
I would recommend publishing the work as the authors clarified most of the concerns.
