Algebraically Approximate And Noisy Realization Of Discrete-time Systems And Digital Images (lecture Notes In Electrical Engineering)
by Yasumichi Hasegawa /
2009 / English / PDF
5.6 MB Download
This monograph deals with approximation and noise cancellation of
dyn- ical systems which include linear and nonlinear input/output
relationships. It also deal with approximation and noise
cancellation of two dimensional arrays. It will be of special
interest to researchers, engineers and graduate students who have
specialized in ?ltering theory and system theory and d- ital
images. This monograph is composed of two parts. Part I and Part II
will deal with approximation and noise cancellation of dynamical
systems or digital images respectively. From noiseless or noisy
data, reduction will be made. A method which reduces model
information or noise was proposed in the reference vol. 376 in
LNCIS [Hasegawa, 2008]. Using this method will allow model
description to be treated as noise reduction or model reduction
without having to bother, for example, with solving many partial
di?er- tial equations. This monograph will propose a new and easy
method which produces the same results as the method treated in the
reference. As proof of its advantageous e?ect, this monograph
provides a new law in the sense of numerical experiments. The new
and easy method is executed using the algebraic calculations
without solving partial di?erential equations. For our
purpose,manyactualexamplesofmodelinformationandnoisereductionwill
also be provided. Using the analysis of state space approach, the
model reduction problem may have become a major theme of technology
after 1966 for emphasizing e?ciency in the ?elds of control,
economy, numerical analysis, and others.
This monograph deals with approximation and noise cancellation of
dyn- ical systems which include linear and nonlinear input/output
relationships. It also deal with approximation and noise
cancellation of two dimensional arrays. It will be of special
interest to researchers, engineers and graduate students who have
specialized in ?ltering theory and system theory and d- ital
images. This monograph is composed of two parts. Part I and Part II
will deal with approximation and noise cancellation of dynamical
systems or digital images respectively. From noiseless or noisy
data, reduction will be made. A method which reduces model
information or noise was proposed in the reference vol. 376 in
LNCIS [Hasegawa, 2008]. Using this method will allow model
description to be treated as noise reduction or model reduction
without having to bother, for example, with solving many partial
di?er- tial equations. This monograph will propose a new and easy
method which produces the same results as the method treated in the
reference. As proof of its advantageous e?ect, this monograph
provides a new law in the sense of numerical experiments. The new
and easy method is executed using the algebraic calculations
without solving partial di?erential equations. For our
purpose,manyactualexamplesofmodelinformationandnoisereductionwill
also be provided. Using the analysis of state space approach, the
model reduction problem may have become a major theme of technology
after 1966 for emphasizing e?ciency in the ?elds of control,
economy, numerical analysis, and others.
