Abstract
Measuring large batches of solution concentrations is a cumbersome task that is time consuming and involves many reagents. Determining how to improve the measurement efficiency of batch concentrations is an urgent problem to be solved. This paper introduces an efficient method for the measurement of batch solution concentrations based on normalized compressed sensing. The method is based on the sparsity of natural signals and can reconstruct the original batch concentration signals with a high level of accuracy while taking fewer measurements. The proposed method extracts subsamples from the original samples according to a sampling matrix; the number of subsamples can be much smaller than the original number of samples. Then the solution concentration of the original samples can be reconstructed by measuring the subsamples. The specific process includes sparse signal representation, non-related observation, and nonlinear optimization reconstruction. Compared with the traditional measurement method, the proposed method is demonstrably superior for the measurement of batch solution concentrations; satisfactory batch solution concentration distribution results can be obtained with a number of measurements that is much smaller than the number of samples. The proposed method will greatly reduce the time and cost of measurement.
Highlights
Compressed sensing is a technology at the forefront of the fields of fast magnetic resonance imaging,[1,2] image denoising,[3,4,5] single-pixel camera development,[6] and so on
In this paper, compressed sensing is used for batch solution concentration measurement
The compressed sensing method is introduced into batch solution concentration measurement to solve the above problem
Summary
Compressed sensing is a technology at the forefront of the fields of fast magnetic resonance imaging,[1,2] image denoising,[3,4,5] single-pixel camera development,[6] and so on. The compressed sensing method is introduced into batch solution concentration measurement to solve the above problem. The proposed method reduces the number of measurements by using normalized compressed sampling of the original batch concentration signals and can obtain a satisfactory solution concentration. The sample values of the fluoride ion concentrations corresponding to different row vectors in the sampling matrix are measured according to the equation m = rV, where m is the mass of the sampled ions, r is the measured mass concentration of the sampled ions, and V is the total volume of the sampled liquid. The BP,[17] MP, Orthogonal Matching Pursuit (OMP),[19] and other recovery algorithms can be used to reconstruct the fluoride ion concentration distribution in batches of samples.
Sign-in/Register to view highlights & summary 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 callDisclaimer: 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.
