ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349)
DOI: 10.1109/iscas.1999.780096
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Signal analysis of externally linear filters

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Cited by 7 publications
(10 citation statements)
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“…Assume first that the ELIN systems examined in this paper are developed from a linear time-invariant prototype circuit, using a generalization [23], [24] of the state-space mapping method of [4]. Let the minimum dimension state-space equations of an th order prototype be (1) where and are the input and output signals, is the state vector with elements, and is its time derivative.…”
Section: Perturbation Analysismentioning
confidence: 99%
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“…Assume first that the ELIN systems examined in this paper are developed from a linear time-invariant prototype circuit, using a generalization [23], [24] of the state-space mapping method of [4]. Let the minimum dimension state-space equations of an th order prototype be (1) where and are the input and output signals, is the state vector with elements, and is its time derivative.…”
Section: Perturbation Analysismentioning
confidence: 99%
“…Using the chain rule of differentiation, it follows that (6) with denoting the Jacobian matrix 1 of mapping . Substituting (5) and (6) into (1) we obtain (7) In case , the Jacobian matrix is square and assuming that is a nonsingular matrix, premultiplying both sides of the first of (7) with the inverse of , we obtain the state-space equations of a minimum dimension externally linear system [23], [24]. Instantaneous companding filters are typical examples of minimum dimension systems.…”
Section: Perturbation Analysismentioning
confidence: 99%
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