On the performance enhancement of adaptive signal averaging: A means for improving the sensitivity and rate of data acquisition in magnetic resonance and other analytical measurements

Abstract

A few years back, our lab developed a signal averaging technique that greatly reduces the number of scans required to achieve a comparable signal-to-noise ratio to that of conventional signal averaging for continuous wave magnetic resonance measurements. We utilize an adaptive filter in a signal averaging scheme without any prior knowledge of the signal under observation. We termed this technique adaptive signal averaging (ASA). The technique was successful in reducing the noise variance by a factor of at least 10 in a single trace and is shown to converge in time by the same factor. ASA can also be useful in many other applications where signal averaging is utilized, such as medical imaging, electrocardiography, or electroencephalography. The purpose of this paper is to describe the advancements made to the technique, present a derivation of its performance enhancement, and illustrate the power of the technique through a set of simulations.