Study for noise performance parameter estimation of TWT electron gun

2016 ◽  
Author(s):  
Shangzheng Gao ◽  
Yuanyuan He ◽  
Hehong Fan ◽  
Changsheng Shen ◽  
Xiaohan Sun ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Performance Parameter ◽  
Electron Gun ◽  
Noise Performance

Noise performance analyses for TWT electron gun

2015 ◽  
Author(s):  
Hehong Fan ◽  
Yuanyuan He ◽  
Xiaohan Sun ◽  
Haihua Gong ◽  
Yixue Wei ◽  
...  
Keyword(s):  
Electron Gun ◽  
Noise Performance ◽  
Performance Analyses

scholarly journals Implementation of D-Spline-Based Incremental Performance Parameter Estimation Method with ppOpen-AT

2014 ◽  
Vol 22 (4) ◽  
pp. 299-307 ◽  
Author(s):  
Teruo Tanaka ◽  
Ryo Otsuka ◽  
Akihiro Fujii ◽  
Takahiro Katagiri ◽  
Toshiyuki Imamura
Keyword(s):  
Parameter Estimation ◽  
Sparse Matrix ◽  
Estimation Method ◽  
Block Size ◽  
Performance Parameter ◽  
Performance Tuning ◽  
Performance Parameters ◽  
Parameter Estimation Method ◽  
Matrix Vector Multiplication ◽  
Time Required

In automatic performance tuning (AT), a primary aim is to optimize performance parameters that are suitable for certain computational environments in ordinary mathematical libraries. For AT, an important issue is to reduce the estimation time required for optimizing performance parameters. To reduce the estimation time, we previously proposed the Incremental Performance Parameter Estimation method (IPPE method). This method estimates optimal performance parameters by inserting suitable sampling points that are based on computational results for a fitting function. As the fitting function, we introduced d-Spline, which is highly adaptable and requires little estimation time. In this paper, we report the implementation of the IPPE method with ppOpen-AT, which is a scripting language (set of directives) with features that reduce the workload of the developers of mathematical libraries that have AT features. To confirm the effectiveness of the IPPE method for the runtime phase AT, we applied the method to sparse matrix–vector multiplication (SpMV), in which the block size of the sparse matrix structure blocked compressed row storage (BCRS) was used for the performance parameter. The results from the experiment show that the cost was negligibly small for AT using the IPPE method in the runtime phase. Moreover, using the obtained optimal value, the execution time for the mathematical library SpMV was reduced by 44% on comparing the compressed row storage and BCRS (block size 8).

An Improved Return Maps Method for Parameter Estimation of Chaotic Systems

2020 ◽  
Vol 30 (04) ◽  
pp. 2050058
Author(s):  
Yuexi Peng ◽  
Kehui Sun ◽  
Shaobo He
Keyword(s):  
Parameter Estimation ◽  
Euclidean Distance ◽  
Chaotic Systems ◽  
Differential Evolution Algorithm ◽  
Noise Performance ◽  
Practical Applications ◽  
Return Maps ◽  
Comparison Results ◽  
Calculation Process ◽  
Evolution Algorithm

Recently, an effective method called return maps is proposed for the parameter estimation of chaotic systems. However, high time-consumption limits practical applications. In this paper, we focus on this problem, and an improved return maps method is proposed. It combines the differential evolution algorithm with the return maps method, and simplifies the calculation process of Euclidean distance. Numerical simulations are carried out on two fractional-order chaotic systems, and the other five methods are used as the comparison. Results show that the improved method can accurately estimate the parameters of chaotic systems, and it saves much time than does the classical return maps method. Furthermore, the proposed method also exhibits good anti-noise performance.

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