代码搜索：implementing
找到约 2,669 项符合「implementing」的源代码
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www.eeworm.com/read/281694/9139755
m regrweight.m
function [X,backmap] = RegrWeight(DATA,w)
% [X] = RegrWeight(DATA,w)
%
% Function for weighting different samples
% (for implementing weighted least squares
% or compensation of heterosceda
www.eeworm.com/read/375399/9361881
readme
This software distribution contains the MATLAB code implementing the optimal
filter bank design algorithms described in the following paper:
Yi Chen, Michael D. Adams, and Wu-Sheng Lu,
"D
www.eeworm.com/read/175308/9552774
ex-08-02
//Example 08-02: Extending and combining interfaces
using System;
interface IStorable
{
void Read();
void Write(object obj);
int Status { get; set; }
}
// here's the new inter
www.eeworm.com/read/175308/9552776
ex-08-05
//Example 08-05: Explicit implementation
using System;
interface IStorable
{
void Read();
void Write();
}
interface ITalk
{
void Talk();
void Read();
}
// Simplify
www.eeworm.com/read/362735/9984255
cpp brctlsampleapplayoutobserver.cpp
/*
* ============================================================================
* Name : BrCtlSampleAppLayoutObserver.cpp
* Part of : BrCtlSampleApp
* Interface : Browser Control
www.eeworm.com/read/159921/10587927
m contents.m
% Statistical learning methods.
%
% Included directories (implementing algorithms):
% minimax - (dir) Minimax learning algorithm.
% unsuper - (dir) Unsupervised learning methods, EM algori
www.eeworm.com/read/421949/10676625
m contents.m
% Statistical learning methods.
%
% Included directories (implementing algorithms):
% minimax - (dir) Minimax learning algorithm.
% unsuper - (dir) Unsupervised learning methods, EM algori
www.eeworm.com/read/154303/7107071
txt ex7_27.txt
Example 7.27 Implementing the Composite Transfer Object
public class ResourceCompositeTO {
private ResourceTO resourceData;
private Collection skillSets;
private Collection blockOutTimes;
www.eeworm.com/read/438496/7730809
nfo lib.nfo
驰哪跘rtech.House.Implementing.Electronic.Card.Payment.Systems.eBook-LiB勰嫩
www.eeworm.com/read/321771/13399487
m regrweight.m
function [X,backmap] = RegrWeight(DATA,w)
% [X] = RegrWeight(DATA,w)
%
% Function for weighting different samples
% (for implementing weighted least squares
% or compensation of heterosceda