代码搜索：Nearest
找到约 1,596 项符合「Nearest」的源代码
代码结果 1,596
www.eeworm.com/read/139007/13195411
m skewpart.m
function S = skewpart(A)
%SKEWPART Skew-symmetric (skew-Hermitian) part.
% SKEWPART(A) is the skew-symmetric (skew-Hermitian) part of A,
% (A - A')/2.
% It is the neare
www.eeworm.com/read/403808/11509095
f90 cvt_mesh.f90
program main
!*****************************************************************************80
!
!! MAIN is the main program for CVT_TET_MESH.
!
! Discussion:
!
! CVT_TET_MESH uses CVT sampling on
www.eeworm.com/read/174450/9587168
cpp sparsematrixongpu2.cpp
// SparseMatrixOnGPU2.cpp: implementation of the SparseMatrixOnGPU2 class.
//
//////////////////////////////////////////////////////////////////////
#include "stdafx.h"
#include "shadow.h"
#inc
www.eeworm.com/read/386050/8767506
m knnr.m
%KNNR Nearest neighbor regression
%
% Y = KNNR(X,K)
%
% INPUT
% X Regression dataset
% K number of neighbors (default K=3)
%
% OUTPUT
% Y k-nearest neighbor regression
%
% DESCRIPTIO
www.eeworm.com/read/284304/8947909
m ans4_15.m
% Interpolation using the four methods
x=[1 1.1 1.2 1.3 1.4];
y=[1.00000 1.23368 1.55271 1.99372 2.61170];
length_of_x=length(x);
scalar_x=x(1):0.05:x(length_of_x);
length_of_sx=length(scalar_x);
www.eeworm.com/read/426535/9014882
m ex1606.m
%例16-6 二维插值方法效果比较
[x,y] = meshgrid(-3:1:3); %产生已知数据栅格点
z = peaks(x,y); %计算已知点上的函数值
surf(x,y,z) %画基于已知数据点的三维表面图，如图16-8
title('graphic based on original data') %对图形加标题
[xi,yi] = meshgrid(-3:0.25:3
www.eeworm.com/read/357617/10204986
m ans5_4.m
% Interpolation using the four methods
x=[1 1.1 1.2 1.3 1.4];
y=[1.00000 1.23368 1.55271 1.99372 2.61170];
length_of_x=length(x);
scalar_x=x(1):0.05:x(length_of_x);
length_of_sx=length(scalar_x);
www.eeworm.com/read/417309/10996151
m ans5_4.m
% Interpolation using the four methods
x=[1 1.1 1.2 1.3 1.4];
y=[1.00000 1.23368 1.55271 1.99372 2.61170];
length_of_x=length(x);
scalar_x=x(1):0.05:x(length_of_x);
length_of_sx=length(scalar_x);
www.eeworm.com/read/449504/7502923
m compare_weights.m
% PURPOSE: An example of model comparison using far_g() function
% to compare various weight matrix specifications
% (on a small data set)
%---------------------
www.eeworm.com/read/441245/7672695
m knnr.m
%KNNR Nearest neighbor regression
%
% Y = KNNR(X,K)
%
% INPUT
% X Regression dataset
% K number of neighbors (default K=3)
%
% OUTPUT
% Y k-nearest neighbor regression
%
% DESCRIPTIO