A General Neural Network-Based Approach to Modeling Sensors in PSPICE Simulation
Lianming Wang, Yun Lin, Ying Huang · 2007
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.