Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/220333
Title: Volterra Series-Based Time-Domain Macromodeling of Nonlinear Circuits
Authors: Xiaoyan Y. Z. Xiong;Li Jun Jiang;Jos&x00E9; E. Schutt-Ain&x00E9;;Weng Cho Chew
Year: 2017
Publisher: IEEE
Abstract: Volterra series (VS) representation is a powerful mathematical model for nonlinear circuits. However, the difficulties in determining higher order Volterra kernels limited its broader applications. In this paper, a systematic approach that enables a convenient extraction of Volterra kernels from X-parameters is presented. A concise and general representation of the output response due to arbitrary number of input tones is given. The relationship between Volterra kernels and X-parameters is explicitly formulated. An efficient frequency sweep scheme and an output frequency indexing scheme are provided. The least square linear regression method is employed to separate different orders of Volterra kernels at the same frequency, which leads to the obtained Volterra kernels complete. The proposed VS representation based on X-parameters is further validated for time-domain verification. The proposed method is systematic and general-purpose. It paves the way for time-domain simulation with X-parameters and constitutes a powerful supplement to the existing blackbox macromodeling methods for nonlinear circuits.
URI: http://localhost/handle/Hannan/220333
volume: 7
issue: 1
More Information: 39,
49
Appears in Collections:2017

Files in This Item:
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7763759.pdf2.64 MBAdobe PDF
Title: Volterra Series-Based Time-Domain Macromodeling of Nonlinear Circuits
Authors: Xiaoyan Y. Z. Xiong;Li Jun Jiang;Jos&x00E9; E. Schutt-Ain&x00E9;;Weng Cho Chew
Year: 2017
Publisher: IEEE
Abstract: Volterra series (VS) representation is a powerful mathematical model for nonlinear circuits. However, the difficulties in determining higher order Volterra kernels limited its broader applications. In this paper, a systematic approach that enables a convenient extraction of Volterra kernels from X-parameters is presented. A concise and general representation of the output response due to arbitrary number of input tones is given. The relationship between Volterra kernels and X-parameters is explicitly formulated. An efficient frequency sweep scheme and an output frequency indexing scheme are provided. The least square linear regression method is employed to separate different orders of Volterra kernels at the same frequency, which leads to the obtained Volterra kernels complete. The proposed VS representation based on X-parameters is further validated for time-domain verification. The proposed method is systematic and general-purpose. It paves the way for time-domain simulation with X-parameters and constitutes a powerful supplement to the existing blackbox macromodeling methods for nonlinear circuits.
URI: http://localhost/handle/Hannan/220333
volume: 7
issue: 1
More Information: 39,
49
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7763759.pdf2.64 MBAdobe PDF
Title: Volterra Series-Based Time-Domain Macromodeling of Nonlinear Circuits
Authors: Xiaoyan Y. Z. Xiong;Li Jun Jiang;Jos&x00E9; E. Schutt-Ain&x00E9;;Weng Cho Chew
Year: 2017
Publisher: IEEE
Abstract: Volterra series (VS) representation is a powerful mathematical model for nonlinear circuits. However, the difficulties in determining higher order Volterra kernels limited its broader applications. In this paper, a systematic approach that enables a convenient extraction of Volterra kernels from X-parameters is presented. A concise and general representation of the output response due to arbitrary number of input tones is given. The relationship between Volterra kernels and X-parameters is explicitly formulated. An efficient frequency sweep scheme and an output frequency indexing scheme are provided. The least square linear regression method is employed to separate different orders of Volterra kernels at the same frequency, which leads to the obtained Volterra kernels complete. The proposed VS representation based on X-parameters is further validated for time-domain verification. The proposed method is systematic and general-purpose. It paves the way for time-domain simulation with X-parameters and constitutes a powerful supplement to the existing blackbox macromodeling methods for nonlinear circuits.
URI: http://localhost/handle/Hannan/220333
volume: 7
issue: 1
More Information: 39,
49
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7763759.pdf2.64 MBAdobe PDF