2017
DOI: 10.1109/tcsii.2016.2557238
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FSRFT—Fast Simplified Real Frequency Technique via Selective Target Data Approach for Broadband Double Matching

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Cited by 17 publications
(24 citation statements)
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“…The polynomial must be a strictly Hurwitz polynomial for obtaining realizable networks and can be obtained from even polynomial by where is the 1 st coefficient of the polynomial and Matlab command represents a polynomial constructed of left half plane roots selected among the roots of the polynomial . is written in a form of [1,7], (7)  Compute scattering matrix in Belevitch form by (8) where is unimodular constant ( ) [1,7]. In SRFT formalism, the ultimate aim of designing an equalizer is to be able to optimize the coefficients of the numerator polynomial of the input reflection function (9)  Compute the gain via (10)…”
Section: ) Optimization Functionmentioning
confidence: 99%
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“…The polynomial must be a strictly Hurwitz polynomial for obtaining realizable networks and can be obtained from even polynomial by where is the 1 st coefficient of the polynomial and Matlab command represents a polynomial constructed of left half plane roots selected among the roots of the polynomial . is written in a form of [1,7], (7)  Compute scattering matrix in Belevitch form by (8) where is unimodular constant ( ) [1,7]. In SRFT formalism, the ultimate aim of designing an equalizer is to be able to optimize the coefficients of the numerator polynomial of the input reflection function (9)  Compute the gain via (10)…”
Section: ) Optimization Functionmentioning
confidence: 99%
“…where (13) and 14where are the elements of the unitnormalized scattering matrix of the equalizer E. and are generator and load reflectances expressed in terms of generator and load impedances and [1,7]. and are input and output reflectance functions, respectively, seen at the related port of the matching network when the other port is terminated with and , respectively [1,21]. A much simpler and handy impedance based gain formulae which are equivalent to the reflectance based gain formulae given in (10) and (11) can also be used to calculate the gain such that [21]…”
Section: ) Optimization Functionmentioning
confidence: 99%
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