A demonstration of deterministic jitter (DJ) deconvolution

Author

Sun, Jie ; Li, Mike ; Wilstrup, Jan

Author_Institution

Wavecrest Corp., San Jose, CA, USA

Volume

1

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

293

Abstract

It is well accepted that the total jitter (TJ) probability density function (PDF) can be represented as a convolution of the deterministic jutter (DJ) PDF and the random Jitter (RJ) PDF [1]. Theoretically, assuming the RJ PDF is known, the DJ PDF can be extracted from the TJ PDF through a deconvolution process. However, practicafly, deconvolution process has shown to be very difficult. The purpose of this paper is to demonstrate for the first time a detailed DJ PDF, which has a real distribution (not only the simple double-delta model). A time-domain linear equation/matrix formulation for the convolution is adopted to illustrate the deconvolution process, and the DJ PDF is extracted.

Keywords

Gaussian distribution; Toeplitz matrices; deconvolution; determinants; inverse problems; jitter; least squares approximations; smoothing methods; time-domain analysis; Toeplitz matrix; deterministic jitter deconvolution; forward problem; inverse problem; least squares solution; normalized single Gaussian distribution; random Jitter; real distribution; signal integrity; smoothing operation; stochastic processes; time-domain linear equation/matrix formulation; total jitter probability density function; Bit rate; Convolution; Deconvolution; Equations; Jitter; Least squares methods; Probability density function; SONET; Stochastic processes; Time domain analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2002. IMTC/2002. Proceedings of the 19th IEEE

ISSN

1091-5281

Print_ISBN

0-7803-7218-2

Type

conf

DOI

10.1109/IMTC.2002.1006856

Filename

1006856