This folder contains all the codes based on Matlab Language for the book <《Iterative Methods for Linear and Nonlinear Equations》, and there are totally 21 M files, which can solve most of linear and nonlinear equations problems.
tServer task executes functions at low priority (254). serverSend
funtion is used to send a request to the tServer to execute a
function at the tServer s priority.
First tServer task executes the i() system call to print the summary
of tShell task. Next an address exception is caused in tServer
task by trying to execute a funtion at non-aligned word boundry.
As a result SIGBUS signal is raised automatically. Signals
(setjmp() and longjmp()) are used to allow the tServer task to
recover gracefully from an address error exception. For more
information about signals, please refer to sigLib manual pages.
Robustnesstochangesinilluminationconditionsaswellas viewing perspectives is an important requirement formany computer vision applications. One of the key fac-ors in enhancing the robustness of dynamic scene analy-sis that of accurate and reliable means for shadow de-ection. Shadowdetectioniscriticalforcorrectobjectde-ection in image sequences. Many algorithms have beenproposed in the literature that deal with shadows. How-ever,acomparativeevaluationoftheexistingapproachesisstill lacking. In this paper, the full range of problems un-derlyingtheshadowdetectionareidenti?edanddiscussed.Weclassifytheproposedsolutionstothisproblemusingaaxonomyoffourmainclasses, calleddeterministicmodeland non-model based and statistical parametric and non-parametric. Novelquantitative(detectionanddiscrimina-ionaccuracy)andqualitativemetrics(sceneandobjectin-dependence,?exibilitytoshadowsituationsandrobustnesso noise) are proposed to evaluate these classes of algo-rithms on a benchmark suite of indoor and outdoor videosequences.
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!-- Fortran code for FDTD with Berenger PMLs, version 1.0, May 1999
!-- by Jos Bergervoet.
!-- Plot field and/or Poynting vector S around radiating linear dipole
vTools is a toolbox for Matlab 5.3 developed
within the Department of Electrical Systems and
Automation (DSEA) of the University of Pisa (Italy)
with the aim to offering to the Matlab users
(especially control engineers and control
engineering students) a completely graphical
toolbox for linear system analysis and robust
control synthesis
MATLAB PROGRAMS FOR "VIBRATION SIMULATION USING MATLAB AND ANSYS"
All the M-files which are listed in the book are available on this site. The
ANSYS-related files and some non-listed utility M-files are available for download
from the author s website, www.hatchcon.con.
In 1960, R.E. Kalman published his famous paper describing a recursive solution
to the discrete-data linear filtering problem. Since that time, due in large part to advances
in digital computing, the Kalman filter has been the subject of extensive research
and application, particularly in the area of autonomous or assisted
navigation.
In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata
linear filtering problem [Kalman60]. Since that time, due in large part to advances in digital
computing, the
Kalman filter
has been the subject of extensive research and application,
particularly in the area of autonomous or assisted navigation. A very “friendly” introduction to the
general idea of the Kalman filter can be found in Chapter 1 of [Maybeck79], while a more complete
introductory discussion can be found in [Sorenson70], which also contains some interesting
historical narrative.
Welcome to the ASTA 3 Help Tutorials. These are documented tutorials that included new user jump start, to file sends to server techniques with non-database servers showing how to use Providers and ServerMethods. A Current version of these tutorials can always be found on line
his paper provides a tutorial and survey of methods for parameterizing
surfaces with a view to applications in geometric modelling and computer graphics.
We gather various concepts from di® erential geometry which are relevant to surface
mapping and use them to understand the strengths and weaknesses of the many
methods for parameterizing piecewise linear surfaces and their relationship to one
another.
