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Peer-Review Record

Temperature Field Reconstruction Method for Acoustic Tomography Based on Multi-Dictionary Learning

Sensors 2023, 23(1), 208; https://doi.org/10.3390/s23010208
by Yuankun Wei *, Hua Yan and Yinggang Zhou
Reviewer 1:
Reviewer 2: Anonymous
Sensors 2023, 23(1), 208; https://doi.org/10.3390/s23010208
Submission received: 8 November 2022 / Revised: 21 December 2022 / Accepted: 22 December 2022 / Published: 25 December 2022
(This article belongs to the Section Sensing and Imaging)

Round 1

Reviewer 1 Report

1. Why some of the paragraphs have background with green color?

2. The algorithm based on MDL for AT should have the application limits, such as the temperature distribution is sparse.

3. In introduction, the description of other related algorithms based on sparsity is lack.

4. The unit of abscissa variable is missing in Figs. 2 and 5.

5. In Figure 2, the model of 2-peak is maybe wrong.

6. The size of the sensor in Figure 4 should be given. Is the same as the size used in simulation?

7. The reconstructed results with noise-containment TOFs in simulation should be discussed.

8. The precision of OMP algorithm is not high although the speed is fast. Why the authors do not consider convex optimization algorithm?

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

 

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

the authors  have made good modifications. The size of experimental device in  Fig. 5 should be supplemented, not the size of the sensors in Fig. 3.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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