代码搜索：dirichlet
找到约 330 项符合「dirichlet」的源代码
代码结果 330
www.eeworm.com/read/154760/11928946
m fskernel.m
function y = fskernel(ty,n,n0)
% FSKERNEL Fourier Series smoothing kernel.
%
% Y = FSKERNEL(TY,N,N0) returns the Fourier series smoothing kernel
% TY = kernel type TY = 'd' (Dirichlet) or TY = 'f
www.eeworm.com/read/154209/11983380
m diric.m
function y=diric(x,N)
%DIRIC Dirichlet, or periodic sinc function
% Y = DIRIC(X,N) returns a matrix the same size as X whose elements
% are the Dirichlet function of the elements of X. Positiv
www.eeworm.com/read/341613/12075851
m 3-6.m
%例程3-6 产生Dirichlet函数波形
t=[-4*pi:0.1:4*pi];
x=diric(t,7);
y=diric(t,6);
subplot(2,1,1);
plot(t,x);
subplot(2,1,2);
plot(t,y);
www.eeworm.com/read/415746/11055954
m 3-6.m
%例程3-6 产生Dirichlet函数波形
t=[-4*pi:0.1:4*pi];
x=diric(t,7);
y=diric(t,6);
subplot(2,1,1);
plot(t,x);
subplot(2,1,2);
plot(t,y);
www.eeworm.com/read/146577/12638483
h pde.h
//Copyright (c) 2004-2005, Baris Sumengen
//All rights reserved.
//
// CIMPL Matrix Performance Library
//
//Redistribution and use in source and binary
//forms, with or without modification, ar
www.eeworm.com/read/108859/15573907
m fskernel.m
function y = fskernel(ty,n,n0)
% FSKERNEL Fourier Series smoothing kernel.
%
% Y = FSKERNEL(TY,N,N0) returns the Fourier series smoothing kernel
% TY = kernel type TY = 'd' (Dirichlet) or TY = 'f
www.eeworm.com/read/140847/5779275
m bayesian_score_cpd.m
function score = bayesian_score_CPD(CPD, local_ev)
% bayesian_score_CPD Compute the Bayesian score of a tabular CPD using uniform Dirichlet prior
% score = bayesian_score_CPD(CPD, local_ev)
%
% The Ba
www.eeworm.com/read/140847/5779284
m tabular_cpd.m
function CPD = tabular_CPD(bnet, self, varargin)
% TABULAR_CPD Make a multinomial conditional prob. distrib. (CPT)
%
% CPD = tabular_CPD(bnet, node) creates a random CPT.
%
% The following argume
www.eeworm.com/read/133943/5897459
m bayesian_score_cpd.m
function score = bayesian_score_CPD(CPD, local_ev)
% bayesian_score_CPD Compute the Bayesian score of a tabular CPD using uniform Dirichlet prior
% score = bayesian_score_CPD(CPD, local_ev)
%
% The Ba
www.eeworm.com/read/133943/5897468
m tabular_cpd.m
function CPD = tabular_CPD(bnet, self, varargin)
% TABULAR_CPD Make a multinomial conditional prob. distrib. (CPT)
%
% CPD = tabular_CPD(bnet, node) creates a random CPT.
%
% The following argume