Title :
A General Neural Network-Based Approach to Modeling Sensors in PSPICE Simulation
Author :
Wang, Lian Ming ; Ma, Ling Yun ; Huang, Ying
Author_Institution :
Northeast Normal Univ., Changchun
Abstract :
Most sensors can not be modeled easily, which leads to the problem that a circuit with sensors can not be simulated in PSPICE. A method based on the neural network for modeling sensors in PSPICE is presented to solve the problem. Firstly, a multi-layer feedforward neural network is used to approximate the characteristics of a sensor. Secondly, the achieved structure of the neural network is described in the PSPICE language to form a subcircuit. Finally, the subcircuit is used as the sensor model when the changes of a non-electric quantity imposed on the sensor in real applications is replaced with that of an electric quantity in PSPICE simulation. The availability of this method is exemplified by modeling a negative temperature coefficient (NTC) thermistor.
Keywords :
SPICE; feedforward neural nets; neural chips; PSPICE simulation; multilayer feedforward neural network; sensor; temperature coefficient thermistor; Circuit simulation; Feedforward neural networks; Feeds; Libraries; Multi-layer neural network; Neural networks; Piecewise linear approximation; SPICE; Sensor phenomena and characterization; Thermistors;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.32
