Abstract

This paper reviews the current use of spectroscopy and related instrumentation in chemical analysis. Advancements in digital signal processing technology are making it possible to improve the sensitivity and accuracy of analytical instruments without expensive upgrading of instrument hardware. A hybrid neural network (HNN) is described that can perform nonlinear signal analysis. The HNN approach combines the simple data reduction capability of conventional linear signal processing algorithms with the adaptive learning and recognition ability of a multilayer nonlinear neural network architecture. A number of examples show the rise of the HNN for environmental monitoring and real-time process control.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.