Cosparse Analysis Model-Based Compressive Sensing With Optimized Projection Matrix

2021 ◽  
Vol 69 (11) ◽  
pp. 113-121
Author(s):  
Endra Oey ◽  
Dadang Gunawan ◽  
Dodi Sudiana
Keyword(s):  
Compressive Sensing ◽  
Projection Matrix ◽  
Analysis Model ◽  
Model Based

scholarly journals Projection Matrix Design for Co-Sparse Analysis Model Based Compressive Sensing

2018 ◽  
Vol 159 ◽  
pp. 01061
Author(s):  
Endra Oey ◽  
Dadang Gunawan ◽  
Dodi Sudiana
Keyword(s):  
Compressive Sensing ◽  
Projection Matrix ◽  
Signal Quality ◽  
Tight Frames ◽  
Analysis Model ◽  
Mutual Coherence ◽  
Model Based ◽  
Equiangular Tight Frames ◽  
Simulation Results ◽  
Matrix Design

Co-sparse analysis model based-compressive sensing (CAMBCS) has gained attention in recent years as alternative to conventional sparse synthesis model based (SSMB)-CS. The equivalent operator as counterpart of the equivalent dictionary in the SSMB-CS is introduced in the CAMB-CS as the product of projection matrix and transpose of the analysis dictionary. This paper proposes an algorithm for designing suitable projection matrix for CAMB-CS by minimizing the mutual coherence of the equivalent operator based on equiangular tight frames design. The simulation results show that the CAMB-CS with the proposed projection matrix outperforms the SSMB-CS in terms of the signal quality reconstruction.

Regional effect of monetary policy based on GVAR model and machine learning

2020 ◽  
pp. 1-13
Author(s):  
Zengming Zhao ◽  
Wenting Chen
Keyword(s):  
Machine Learning ◽  
Growth Rate ◽  
Monetary Policy ◽  
Stress Test ◽  
Analysis Model ◽  
Conduction Model ◽  
Regional Effect ◽  
Macroeconomic Factors ◽  
Model Based ◽  
Gray Correlation

Monetary policy is an important means for a country to regulate macroeconomic operations and achieve established economic goals. Moreover, a reasonable monetary policy improves the efficiency of financial operations on a global scale and effectively resolves the financial crisis. At present, scholars from various countries have begun to pay attention to the issue of differentiated formulation of monetary policy among regions. This paper combines machine learning to construct a monetary policy differentiation effect analysis model based on the GVAR model. Moreover, this paper uses the gray correlation analysis method to obtain the gray correlation matrix between industries, and then introduces the industry’s own characteristics, industry relevance and macroeconomic factors into the macro stress test of credit risk. In addition, this paper constructs a conduction model based on the industry GVAR model, and uses the first-order difference sequence of GDP growth rate, CPI growth rate and M2 growth rate of each economic region to construct a GVAR model to test the impulse response function. The results of the test show that the monetary policy shocks of various economic regions are significantly different. All in all, the research results show that the performance of the model constructed in this paper is good.

Screening blood donors for hereditary hemochromatosis: Decision analysis model based on a 30-year database

1995 ◽  
Vol 109 (1) ◽  
pp. 177-188 ◽  
Author(s):  
Paul C. Adams ◽  
James C. Gregor ◽  
Ann E. Kertesz ◽  
Leslie S. Valberg
Keyword(s):  
Decision Analysis ◽  
Blood Donors ◽  
Hereditary Hemochromatosis ◽  
Decision Analysis Model ◽  
Analysis Model ◽  
Model Based
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