Simultaneous quantification of Cd2+ and Pb2+ in solution has been correctly targeted using the kinetic information from a single non-specific potentiometric sensor. Dual quantification was accomplished from the complex information in the transient response of an electrode used in a Sequential Injection Analysis (SIA) system and recorded after step injection of sample. Data was firstly preprocessed with the Discrete Wavelet Transform (DWT) to extract significant features and then fed into an Artificial Neural Network (ANN) for building the calibration model. DWT stage was optimized regarding the wavelet function and decomposition level, while the ANN stage was optimized on its structure. To simultaneously corroborate the effectiveness of the approach, two different potentiometric sensors were used as study case, one using a glass selective to Cd2+ and another a PVC membrane selective to Pb2+. © 2009 Elsevier B.V. All rights reserved.
|Publication status||Published - 1 Jan 2010|
- Artificial neural networks
- Multi-analyte calibration
- Wavelet transform