电容压力传感器的函数链接型神经网络建模方法

旨在开发一种计算简单的电容压力传感器的模型，以便经济、可靠地应用。分析表明，采用新型函数链接型神经网络建立的电容压力传感器模型，能够精确读出应用压力。它是一种能实现输入到输出的高度非线性映射并且运算高效的非线性网络，在建立传感器模型的类似性能上比多层感知器具有更高的运算优势。

Method for Modeling of Capacitor Pressure Sensor Using FLANN

The prime aim of this paper is to develop a model of the capacitor pressure sensor involving less computational complexity, so that its implementation could be economical and robust. It is shown that a CPS can be modeled for accurate readout of applied pressure using a novel functional link artificial neural network. The proposed FLANN is a computationally efficient nonlinear network and is capable of complex nonlinear mapping between its input and output pattern space. The FLANN offers substantial computational advantage over a multiplayer perceptron for similar performance in modeling of the CPS.