Improving the detection sensitivity of chromatography by stochastic resonance

Abstract

Improving the detection sensitivity of analytical instruments has been a challenging task for chemometricians since undetectability has been almost unavoidable in trace analysis, even under optimized experimental conditions and with the use of modern instruments. Various chemometrics methods have been developed which attempt to address this detection problem but with limited success (e.g., fast Fourier transform and wavelet transform). However, the application of stochastic resonance (SR) creates an entirely new and effective methodology. Stochastic resonance is a phenomenon which is manifested in non-linear systems where a weak signal can be amplified and optimized with the assistance of noise. In this review, we summarize the use of basic SR, optimization of parameters and its modifications, including periodic modulation stochastic resonance (PSRA), linear modulation stochastic resonance (LSRA), single-well potential stochastic resonance (SSR) and the Duffing oscillator algorithm (DOA) for amplifying sub-threshold small signals. We also review the advantages and the disadvantages of various SR procedures.

Artificial Neural Network classification of operator workload with an assessment of time variation and noise-enhancement to increase performance

“…Noise-resonance is commonly seen in biological systems, including neurons and the brain itself (Wiesenfeld and Moss, 1995 ; Gluckman, 1996 ; McDonnell and Abbott, 2009 ) and can be used in signal detection (Kay, 2000 ; Chen et al, 2007 ). For example the technique has been used for improving the performance of algorithms for detecting micro-calcifications (a key early sign of cancer) in breast mammograms (Peng et al, 2009 ), in radar target classification (Jouny, 2010 ), and is widely used in chromatography (Zhang et al, 2014 ). It has recently been applied to detecting transient signals in the EEG, both evoked and natural (Casson and Rodriguez-Villegas, 2011 ; Sampanna and Mitaim, 2013 ).…”

Weak signal detection method based on Duffing oscillator with adjustable frequency

“…The method of fast Fourier transform (FFT) can improve the detection ability of weak signals, but the frequency resolution is so low that the frequency of the to-be-detected weak signal cannot be decided accurately [7]. In recent years, the weak signal detection using Duffing oscillators has caused wide public concern in the field of weak signal detection due to its low detection signal-to-noise ratios (SNR) and sensitivity to certain periodic signal [8][9][10][11]. For example, Rashtchi et al [12,13] introduced a novel method for detecting the state of the Duffing oscillator, which deeply affects the accuracy of its application.…”