Novel approach to the use of neural networks to solve real-world analytical problems

Jeremy M. Lerner; Thomas Taiwei Lu; David T. Mintzer; Sean Zhao

doi:10.1117/12.206022

3 April 1995 Novel approach to the use of neural networks to solve real-world analytical problems

Jeremy M. Lerner, Thomas Taiwei Lu, David T. Mintzer, Sean Zhao

Proceedings Volume 2386, Ultrasensitive Instrumentation for DNA Sequencing and Biochemical Diagnostics; (1995) https://doi.org/10.1117/12.206022
Event: Photonics West '95, 1995, San Jose, CA, United States

Abstract

This paper describes the general architecture of a hybrid neural network used to identify noisy and extremely complex spectra. A hybrid neural network has been built for environmental monitoring, medical diagnosis, and process control applications. The hybrid neural network consists of preprocessing algorithms to enhance the features of the spectra and an interconnect weight matrix for recognition. Results suggest that the hybrid neural network, through careful design of both the preprocessing algorithms and the neural network architecture, is capable of increasing the detection limit and speed of many analytical instruments.

Citation Download Citation

Jeremy M. Lerner, Thomas Taiwei Lu, David T. Mintzer, and Sean Zhao "Novel approach to the use of neural networks to solve real-world analytical problems", Proc. SPIE 2386, Ultrasensitive Instrumentation for DNA Sequencing and Biochemical Diagnostics, (3 April 1995); https://doi.org/10.1117/12.206022

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