代码搜索：Reduction
找到约 701 项符合「Reduction」的源代码
代码结果 701
www.eeworm.com/read/367160/9778730
out cbb.out
Tests of CGBBRD
(reduction of a general band matrix to real bidiagonal form)
LAPACK VERSION 3.1.1
The following parameter values will be used:
M: 0 0 0 0 1
www.eeworm.com/read/100431/15873809
c sinll.c
/* sinl.c
*
* Circular sine, long double precision
*
*
*
* SYNOPSIS:
*
* long double x, y, sinl();
*
* y = sinl( x );
*
*
*
* DESCRIPTION:
*
* Range reduction is into intervals o
www.eeworm.com/read/191902/8417042
m hdr.m
function [features, targets] = HDR(features, targets, New_dim, region)
%Reduce the dimensions of the data points using the hierarchical dimensionality reduction algorithm
%Inputs:
% train_feature
www.eeworm.com/read/291380/8422317
m noiserschreiber.m
function xr=noiserSchreiber(x,K,L,r,repeat,auto)
%Syntax: xr=noiserSchreiber(x,K,L,r,repeat,auto)
%_______________________________________________
%
% Geometrical noise reduction for a time series
www.eeworm.com/read/189737/8456526
bak ebk&nvsunits.bak
unit LinAlg
tred2 - Householder (tridiagonal) reduction of a real, symmetric matrix }
tqli - QL diagonalization algorithm with implicit shifts for a real tridiaginal symmetric matrix .
Order - S
www.eeworm.com/read/286662/8751619
m hdr.m
function [patterns, targets] = HDR(patterns, targets, New_dim)
%Reduce the dimensions of the data points using the hierarchical dimensionality reduction algorithm
%Inputs:
% train_patterns - Inpu
www.eeworm.com/read/177129/9468739
m hdr.m
function [features, targets] = HDR(features, targets, New_dim, region)
%Reduce the dimensions of the data points using the hierarchical dimensionality reduction algorithm
%Inputs:
% train_feature
www.eeworm.com/read/372113/9521075
m hdr.m
function [patterns, targets] = HDR(patterns, targets, New_dim)
%Reduce the dimensions of the data points using the hierarchical dimensionality reduction algorithm
%Inputs:
% train_patterns - Inpu
www.eeworm.com/read/167879/9948722
m noiserschreiber.m
function xr=noiserSchreiber(x,K,L,r,repeat,auto)
%Syntax: xr=noiserSchreiber(x,K,L,r,repeat,auto)
%_______________________________________________
%
% Geometrical noise reduction for a time series
www.eeworm.com/read/362008/10023765
m hdr.m
function [patterns, targets] = HDR(patterns, targets, New_dim)
%Reduce the dimensions of the data points using the hierarchical dimensionality reduction algorithm
%Inputs:
% train_patterns - Inpu