代码搜索：Parameterization
找到约 62 项符合「Parameterization」的源代码
代码结果 62
www.eeworm.com/read/460969/7236507
makefile
PROG = model_prep
SRCS = allocate_arrays.f90 func_m1_rho.f90 func_ym.f90 int1d.f90 int1d_y.f90 \
mod_atten.f90 mod_const.f90 mod_files.f90 mod_func.f90 \
mod_integration.f90 mod_interfaces.f90 mod_
www.eeworm.com/read/399808/7833719
m canonmargs.m
% [B, BC] = CANONMARGS(G,LXX,LXY,Y) computes the marginal probabilities on
% individual nodes and pairs of adjacent nodes given a factored Gaussian
% distribution with canonical parameterization. G is
www.eeworm.com/read/388600/2548967
tex paper.tex
\footer{SEP--89}
\title{Antialiasing of Kirchhoff operators by reciprocal
parameterization}
\author{Sergey Fomel}
\maketitle
\input{intro}
\section{Overview of existing methods}
I start with re
www.eeworm.com/read/388600/2549219
tex paper.tex
\title{Regularizing seismic inverse
problems by model re-parameterization using plane-wave construction}
\renewcommand{\thefootnote}{\fnsymbol{footnote}}
\lefthead{Fomel \& Guitton}
\righthead{Plane
www.eeworm.com/read/399808/7833728
m canongbp.m
% [B, BC] = CANONGBP(G,LXX,LXY,Y,VERBOSE,SCHED) runs belief propagation
% on an undirected graphical model with Gaussian factors following a
% canonical parameterization. See CANONMARGS for explanatio
www.eeworm.com/read/345785/11792137
txt pcprb4.out.txt
PCPRB4:
PITCON test problem
Freudenstein-Roth function
Number of equations is 2
Number of variables is 3
This is run number 1
PITCON is free to choose parameterization.
No
www.eeworm.com/read/399808/7833711
m canonmarg.m
% CANONMARG Compute the marginal p(xs), where p is a Normal density
% following the canonical parameterization.
% The function call is [NU L] = CANONMARG(NUS,NUT,LSS,LTT,LST) where
% t
www.eeworm.com/read/187067/8858891
c sysln97xend.c
/*
DESCRIPTION
This is the WRS-supplied configuration module for the VxWorks
ln97xEnd (lnPci) END driver. It performs the dynamic parameterization
of the ln97xEnd driver. This technique of 'ju
www.eeworm.com/read/200886/15420664
m invgammapdf.m
% function p = invGammaPdf(x,a,b)
%
% inv-gamma pdf for parameters, a,b, using the Rubin book parameterization
% (which I believe is different than what Matlab uses, for, gampdf, for
% example)
%
% th
www.eeworm.com/read/305190/13777295
m balpem.m
function mfdb = balpem(data,mid,bd,method,varargin)
%BALPEM Identifies a balanced state-space model from input-output data.
%
% BALPEM uses a balanced parameterization to improve on an initial
%