FSRFT-Fast Simplified Real Frequency Technique via Selective Target Data Approach for Broadband Double Matching
| Autor: | Ramazan Kopru |
|---|---|
| Přispěvatelé: | Bölüm Yok, Kopru, Ramazan -- 0000-0002-6706-7352, [Kopru, Ramazan] Isik Univ, Elect Elect Engn Dept, TR-34980 Istanbul, Turkey, Işık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü, Işık University, Faculty of Engineering, Department of Electrical-Electronics Engineering, Köprü, Ramazan |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Computer science
02 engineering and technology Chebyshev filter simplified real frequency technique (SRFT) Ladder synthesis 0202 electrical engineering electronic engineering information engineering network synthesis Constrained optimization STDA Microwave-Amplifiers Equalizers FSRFT Constraint optimization approach Fast simplified real frequency technique Impedance Solver Impedance matching (electric) Broadband communication Low-pass Chebyshev-type equalizer design Chebyshev filters Simplified real frequency techniques Frequency 2.2 GHz Target data set Time 29 s Algorithm Generator (mathematics) Broadband matching Design Matching (graph theory) Speed performance COA Domain (software engineering) Time 0.6 s Selective target data approach Electronic engineering Algorithm design and analysis Low-pass filters Optimisation Electrical and Electronic Engineering Electrical impedance constraint optimization Constraint optimizations Broadband double-matching solver Broad band matching 020208 electrical & electronic engineering Optimization target data set Load impedance Matched filters 020206 networking & telecommunications Fast SRFT Generators Data set Element numbers Networks |
| Popis: | WOS: 000395489200009 This brief introduces a broadband double-matching (DM) solver called fast simplified real frequency technique (FSRFT). FSRFT is essentially a greatly accelerated variant of the well-known classical simplified real frequency technique (SRFT). The basic idea that turns the classical SRFT into a "fast" SRFT relies on two main approaches: the selective target data approach (STDA) and the constraint optimization approach (COA). STDA constructs an optimization target data set formed of only critically selected target data whose element number is equal to or slightly greater than the order of the system unknowns n plus 1, n + 1. In order to exhibit speed performance comparison between SRFT and FSRFT, an example design is considered. An exemplary DM problem, dealing with an n = 6th order low-pass Chebyshev-type equalizer design to match the given generator and load impedances, has been solved by SRFT within 29 s using 90 target data in a typical computer-e.g., Intel 2.20-GHz i7 CPU with 8-GB RAM. On the other hand, the same problem has been solved by the newly proposed FSRFT within only 0.6 s using only n + 1 = 7 critically selected target data in the same computer. FSRFT introduced herein works in any domain, i.e., lumped, distributed, and mixed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|