<sup>252</sup>Cf-source-driven neutron pulse series signal processing based on compressive sensing

Li Pengcheng; Wei Biao; Feng Peng; Wang Jing; Mi Deling; Zhou Mi

doi:10.11884/HPLPB201426.124003

Volume 26 Issue 12

Sep. 2015

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Li Hairong, Jiang Geyang, Jin Lin, et al. Development of dynamic power control system in proton therapy facility[J]. High Power Laser and Particle Beams, 2020, 32: 045108. doi: 10.11884/HPLPB202032.190442

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Li Pengcheng, Wei Biao, Feng Peng, et al. ²⁵²Cf-source-driven neutron pulse series signal processing based on compressive sensing[J]. High Power Laser and Particle Beams, 2014, 26: 124003. doi: 10.11884/HPLPB201426.124003

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²⁵²Cf-source-driven neutron pulse series signal processing based on compressive sensing

doi: 10.11884/HPLPB201426.124003

1.
Key Laboratory of Opto-electronics Technology and System of Ministry of Education,Chongqing University,Chongqing 400044,China

Received Date: 2014-07-15
Rev Recd Date: 2014-09-19
Publish Date: 2014-12-16

Abstract

Abstract

The 252Cf-Source-Driven neutron pulse series have special sparse structure of 0, 1. There is no doubt that it satisfies the general condition of compressive sensing(CS). Unlike conventional compressive sensing approaches, we model the compressive sensing process with bipartite graph, combining with minimal covering of bipartite graph and adding some suitable conditions to the bipartite graph to construct a sparse and uniform measurement matrix. The results show that this new CS reconstruction algorithm is feasible for the 252Cf-source-driven neutron pulse series, and has a better performance than l1 method. Furthermore, this research provides a new approach or method for the signal processing of 252Cf-source-driven neutron pulse series.
- 252Cf-source-driven noise analysis,
- compressive sensing,
- sparsity,
- bipartite graph

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