Screening for Cancer: Theory, Analysis, and Design.

1984 ◽  
Vol 79 (388) ◽  
pp. 959
Author(s):  
Neil Dubin ◽  
David M. Eddy
Keyword(s):  
Theory Analysis ◽  
Analysis And Design

Theory, analysis and design of high order reflective, absorptive filters

2017 ◽  
Vol 11 (6) ◽  
pp. 787-795 ◽  
Author(s):  
Senad Bulja ◽  
Andrei Grebennikov ◽  
Pawel Rulikowski
Keyword(s):  
High Order ◽  
Theory Analysis ◽  
Analysis And Design

Simulation of Digital Radio Mondiale (DRM) Coverage Prediction – A study case with Radio Republik Indonesia (RRI)

2017 ◽  
Vol 4 (1) ◽  
pp. 32-36
Author(s):  
Nabila Husna Shabrina
Keyword(s):  
Service Planning ◽  
Propagation Model ◽  
System Specification ◽  
Theory Analysis ◽  
Digital Radio ◽  
Analysis And Design ◽  
Transmitter Power ◽  
Antenna Type ◽  
Radio Systems ◽  
Coverage Prediction

In this paper, DRM is applied for simulating coverage prediction in Radio Republik Indonesia (RRI). The proposed method is developed by simulating high frequency propagation from RRI Pro 3 transmitter with VOACAP online software. The simulation is undertaken in some different conditions. The variation of antenna type and transmitter power are observed in the simulation. The time of propagation also discussed to predict the coverage. The result shows that the variation of parameter influences the coverage result of DRM propagation in HF band. Changing the antenna type and time of propagation will make impact in the range of coverage while adding power transmitter gives insignificantly effect to the range of coverage. Keywords—DRM, Prediction Coverage, VOACAP REFERENCES [1] ITU R-REP-BS.2144-2009-PDF-E, “Planning parameters and coverage for Digital Radio Mondiale (DRM) broadcasting at frequencies below 30 MHz”, 2009. [2] M. J. Bradley, “Digital Radio Mondiale: System and Receivers”,Roke Manor Research Ltd, UK, 2003 [3] G. Prieto, I. Pichel, D. Guerra, P. Angueira, J.M. Matias, J.L. Ordiales, A. Arrinda, “Digital Radio Mondiale: Broadcasting and Reception”, IEEE Press, 2004. [4] DRM Features, available under http://www.drm.org [5] “Digital Radio Mondiale (DRM); System Specification,” European Telecommunication Standards Institute (ETSI), ETSI TS 101980, 2001. [6] D. Setiawan, “Alokasi Frekuensi, Kebijakan dan Perencanaan Spektrum Indonesia”, Departemen Komunikasi dan Informatika, 2010. [7] P.A Bradley, Th Dambold, P.Suessmann, “Propagation model for HF Radio Service Planning”, HF Radio Systems and Techniques, Conference Publication No 474 0 IEE, 2000. [8] J.J. Carr, “Practical Antenna Handbook 4th Edition”, McGraw Hill, 1990. [9] J.M Matias et al, “DRM (Digital Radio Mondiale) Local Coverage Tests Using the 26 Mhz Broadcasting Band”, IEEE Transactions on Broadcasting, Vol. 53, No. 1, August 2007. [10] C. A. Balanis, “Antenna Theory Analysis and Design”, 2nd ed, John Wiley & Sons, 2005. [11] Keputusan Direktorat Jendral Pos dan Telekomunikasi Nomor 85/DIRJEN/1999, “Spesifikasi Teknis Perangkat Telekomunikasi, Persyaratan Teknis Perangkat Radio Siaran”, Jakarta, 1999.

scholarly journals Comparative Performance Evaluation of an Accuracy-Enhancing Lyapunov Solver

Information ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 215
Author(s):  
Vasile Sima
Keyword(s):  
Correction Term ◽  
Lyapunov Equation ◽  
Computational Effort ◽  
Lyapunov Equations ◽  
Theory Analysis ◽  
Comparative Performance ◽  
Triangular Form ◽  
Analysis And Design ◽  
Technical Details ◽  
Dense Matrices

Lyapunov equations are key mathematical objects in systems theory, analysis and design of control systems, and in many applications, including balanced realization algorithms, procedures for reduced order models, Newton methods for algebraic Riccati equations, or stabilization algorithms. A new iterative accuracy-enhancing solver for both standard and generalized continuous- and discrete-time Lyapunov equations is proposed and investigated in this paper. The underlying algorithm and some technical details are summarized. At each iteration, the computed solution of a reduced Lyapunov equation serves as a correction term to refine the current solution of the initial equation. The best available algorithms for solving Lyapunov equations with dense matrices, employing the real Schur(-triangular) form of the coefficient matrices, are used. The reduction to Schur(-triangular) form has to be done only once, before starting the iterative process. The algorithm converges in very few iterations. The results obtained by solving series of numerically difficult examples derived from the SLICOT benchmark collections for Lyapunov equations are compared to the solutions returned by the MATLAB and SLICOT solvers. The new solver can be more accurate than these state-of-the-art solvers and requires little additional computational effort.

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