Next Article in Journal
A New Low-Voltage Low-Power Dual-Mode VCII-Based SIMO Universal Filter
Next Article in Special Issue
Design of a Novel Double Negative Metamaterial Absorber Atom for Ku and K Band Applications
Previous Article in Journal
LoBEMS—IoT for Building and Energy Management Systems
Previous Article in Special Issue
Calculation and Interpretation of Ground Penetrating Radar for Temperature and Relative Water Content of Seasonal Permafrost in Qinghai-Tibet Platea
 
 
Article
Peer-Review Record

Study of Algorithms for Wind Direction Retrieval from X-Band Marine Radar Images

Electronics 2019, 8(7), 764; https://doi.org/10.3390/electronics8070764
by Hui Wang 1, Haiyang Qiu 1,*, Pengfei Zhi 1, Lei Wang 2, Wei Chen 1, Rizwan Akhtar 1 and Muhammad Asif Zahoor Raja 3
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Electronics 2019, 8(7), 764; https://doi.org/10.3390/electronics8070764
Submission received: 29 April 2019 / Revised: 3 July 2019 / Accepted: 5 July 2019 / Published: 8 July 2019

Round 1

Reviewer 1 Report

See the attached document.

Comments for author File: Comments.pdf

Author Response

Thank you for your kind concern and review comment for this manuscript. Reply see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Would be helpful to compare the running time if you could write what hardware and what programming language were used for the simulations.

line 369: delete "become"

Author Response

The authors will give greatly gratitude to your kind concern and review comments. The hardware is coded by C , and we test our algorithm in Matllab. We will highlight these information in this paper.

we delete "become" in line 369, sorry for this editing mistake.

Round 2

Reviewer 1 Report

- The choice of non-unified metric for the three algorithms is still unjustified. While the algorithms used different approaches/ methodologies they should comply with a similar metric for performance evaluation. Handling the same research problem inherently requires a unified metric for performance.


- Authors are advised to present the algorithm complexity in big-O notation.


- The quality of the images still needs attention.

Author Response

    

Much more thanks for your kindly further comments and suggestions.

(1)We might firstly misunderstanding the word of  "metric",  using different statistic parameters to try to evaluate the performance of 3 algorithms, actually , prior parameters finally work to build the similarity index which is the correlation coefficient , so this value should be  reasonable to act as a uniform performance evaluation metric. We highlight this in the revised paper to make it much more clear when comparing the performance of different algorithms.

(2) We add time complexity analysis in subsection 3.4 ,  before that , we only  give a description of experienced analysis from algorithm flow chart, this time , we calculate the O() for the three algorithms. Thanks for your kind  suggestion, we think complexity analysis should be more quantitative and scientific with these extra content.

(3) we check all figs again , and replot fig10.


Back to TopTop