(Publisher of Peer Reviewed Open Access Journals)

International Journal of Advanced Computer Research (IJACR)

ISSN (Print):2249-7277    ISSN (Online):2277-7970
Volume-5 Issue-18 March-2015
Full-Text PDF
Paper Title : Linearizing the Characteristics of Gas Sensors using Neural Network
Author Name : Gowri shankari B and Neethu P S
Abstract :

The paper describes implementing arbitrary connected neural network with more powerful network architecture to be embedded in inexpensive microcontroller. Our objective is to extend linear region of operation of nonlinear sensors. In order to implement more powerful neural network architectures on microcontrollers, the special Neuron by Neuron computing routine was developed in assembly language to allow fastest and shortest code. Embedded neural network requires hyperbolic tangent with great precision was used as a neuron activation function. Implementing neural network in microcontroller makes superior to other systems in faster response, smaller errors, and smoother surfaces. But its efficient implementation on microcontroller with simplified arithmetic was another challenge. This process was then demonstrated on gas sensor problem as they were mainly used accurately in measuring gas leakage in industry.

Keywords : Microcontroller, non-linear sensor compensation, embedded, neural network, gas sensor.
Cite this article : Gowri shankari B and Neethu P S, " Linearizing the Characteristics of Gas Sensors using Neural Network " , International Journal of Advanced Computer Research (IJACR), Volume-5, Issue-18, March-2015 ,pp.46-51.