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Parametric studies of matched filters to enhance the signal-to-noise ratios of LC-MS-MS peaks [An article from: Analytica Chimica Acta]

This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Chromatographic parameters of reference signals employed in matched filter methods have been studied using numerical experiments to improve the signal-to-noise (S/N) ratios of small liquid chromatography (LC) peaks obtained with electrospray tandem mass spectrometers (MS-MS). These parameters include the width, shape, and S/N ratios of chromatographic peaks used as the reference signal profiles. Our results show the effect of reference peak widths on improving the S/N ratio of chromatographic peaks; the influence of reference peak shapes is negligible. To verify simulation results, various reference signals, including analyte peaks of high concentration standards, internal standard peaks, and artificial Gaussian peaks of different widths, have been employed to enhance signal peaks on real liquid chromatography-tandem mass spectrometry (LC-MS-MS) chromatograms via matched filter methods. Our experimental results demonstrate that the S/N ratio enhancement of chromatographic peaks agree with the simulation predictions. These findings, therefore, suggest that regardless of peak shape, a well-smooth peak with a width close to that of the analyte peak is an adequate reference signal, when matched filter methods are used to improve LC-MS-MS chromatograms. Nevertheless, all methods processed LC-MS-MS peaks in this study do not achieve the ideal improvement ratios estimated with simulation results. We attribute this deficiency to spike-like noise, which have considerable low frequency components riding on LC-MS-MS chromatograms. Matched filtering, which works as a low-pass filter in the frequency domain, cannot effectively eliminate low frequency flicker noise contributed by these spikes. In addition, simple median filtering does not provide adequate improvement despite being able to smooth out most spikes in the chromatograms.

This is the little board that got Roland into trouble in the 1970s, a clone of the Moog VCF. It sounds really, really nice. I also own a later SH-2000 containing the revised filter, it does not sound really, really nice.
I had to replace the op-amp and electrolytic capacitors to bring this filter back from the dead, it was well worth it.
The filter is the middle part between both dotted lines. The left section is the noise generator and the right is a 3080 based VCA.

Nikon N2020 | Nikkor 50mm ?/1.4 AI | Tiffen Red #25 Filter | Kodak TMAX 100

Oh well, I guess I don't have the same name recognition as Hiroshi Sugimoto. I kinda like mine better though, the water has more detail.

I cleaned up dust and dirt in Photoshop, added a slight vignetting, added the gray border, and leveled it about 1.5 degrees. Also added a de-noise filter to give it a more smoothed out look.

Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system.
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Comprehensive but accessible coverage of signal processing theory including probability models, Bayesian inference, hidden Markov models, adaptive filters and Linear prediction models
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