Abstract: The paper addresses a simple and fast new approach to implement Artificial Neural Networks (ANN) models for the MOS transistor into SPICE. The proposed approach involves two steps, the modeling phase of the device by NN providing its input/output patterns, and the SPICE implementation process of the resulting model. Using the Taylor series expansion, a neural based small-signal model is derived. The reliability of our approach is validated through simulations of some circuits in DC and small-signal analyses
This paper presents modeling nanometer MOSFETs by a neural network approach. The principle of this a...
This paper presents modeling nanometer MOSFETs by a neural network approach. The principle of this a...
This study, the modeling and hardware implementation of semiconductor circuit elements very frequent...
Abstract—An ANN-based small-signal equivalent circuit model for 130 nm MOSFET device is proposed in ...
This paper presents a novel technique to develop device models for semiconductor devices which inclu...
are applied to modeling of electronic circuits. ANNs are used for application of the black-box model...
Artificial neural networks (ANNs) are presented for the technology-independent modeling of active de...
Artificial neural networks (ANNs) are presented for the technology-independent modeling of active de...
The artificial neural network (ANN)-based compact modeling methodology is evaluated in the context o...
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process techno...
This paper proposes new method for optimize and verified electric characterization graph of MOSFET b...
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process techno...
The stiffness of power supply circuits with large power distribution networks makes simulation throu...
This paper presents a neural network method to model nanometer MOSFET transistor characteristics, it...
This study, the modeling and hardware implementation of semiconductor circuit elements very frequent...
This paper presents modeling nanometer MOSFETs by a neural network approach. The principle of this a...
This paper presents modeling nanometer MOSFETs by a neural network approach. The principle of this a...
This study, the modeling and hardware implementation of semiconductor circuit elements very frequent...
Abstract—An ANN-based small-signal equivalent circuit model for 130 nm MOSFET device is proposed in ...
This paper presents a novel technique to develop device models for semiconductor devices which inclu...
are applied to modeling of electronic circuits. ANNs are used for application of the black-box model...
Artificial neural networks (ANNs) are presented for the technology-independent modeling of active de...
Artificial neural networks (ANNs) are presented for the technology-independent modeling of active de...
The artificial neural network (ANN)-based compact modeling methodology is evaluated in the context o...
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process techno...
This paper proposes new method for optimize and verified electric characterization graph of MOSFET b...
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process techno...
The stiffness of power supply circuits with large power distribution networks makes simulation throu...
This paper presents a neural network method to model nanometer MOSFET transistor characteristics, it...
This study, the modeling and hardware implementation of semiconductor circuit elements very frequent...
This paper presents modeling nanometer MOSFETs by a neural network approach. The principle of this a...
This paper presents modeling nanometer MOSFETs by a neural network approach. The principle of this a...
This study, the modeling and hardware implementation of semiconductor circuit elements very frequent...