This paper proposes new method for optimize and verified electric characterization graph of MOSFET by using artificial neural network. Optimization using Neural Network (ONN) will compare current-voltage (I-V) Characteristic graph between the TCAD simulation and TSPICE modeling as desire data control a model parameter of BSIM. In this paper, the neural network method is dynamic feedforward Neural Network. After NN training, the best result is at Neural Network architecture of 36-30-10-5 with Mean Squared Error (MSE) of 1e-28 at epoch of 5
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process techno...
The artificial neural network (ANN)-based compact modeling methodology is evaluated in the context o...
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...
An optimal design of semiconductor device and its process uniformity are critical factors affecting ...
An optimal design of semiconductor device and its process uniformity are critical factors affecting ...
This paper presents a neural network method to model nanometer MOSFET transistor characteristics, it...
et al.;IBM;Intel Corporation;Microsoft Research;SGI;University of ReadingICCS 2006: 6th Internationa...
6th International Conference on Computational Science (ICCS 2006) -- MAY 28-31, 2006 -- Reading, ENG...
Neural modeling of transistor current-voltage characteristics is explored as a possible solution to ...
Abstract: The paper addresses a simple and fast new approach to implement Artificial Neural Networks...
In this work, a neural network-based solution to BSIM3v3 MOSFET model is developed to find the most ...
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...
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process techno...
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process techno...
The artificial neural network (ANN)-based compact modeling methodology is evaluated in the context o...
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...
An optimal design of semiconductor device and its process uniformity are critical factors affecting ...
An optimal design of semiconductor device and its process uniformity are critical factors affecting ...
This paper presents a neural network method to model nanometer MOSFET transistor characteristics, it...
et al.;IBM;Intel Corporation;Microsoft Research;SGI;University of ReadingICCS 2006: 6th Internationa...
6th International Conference on Computational Science (ICCS 2006) -- MAY 28-31, 2006 -- Reading, ENG...
Neural modeling of transistor current-voltage characteristics is explored as a possible solution to ...
Abstract: The paper addresses a simple and fast new approach to implement Artificial Neural Networks...
In this work, a neural network-based solution to BSIM3v3 MOSFET model is developed to find the most ...
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...
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process techno...
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process techno...
The artificial neural network (ANN)-based compact modeling methodology is evaluated in the context o...
The stiffness of power supply circuits with large power distribution networks makes simulation throu...