代码搜索：initialisation
找到约 2,024 项符合「initialisation」的源代码
代码结果 2,024
www.eeworm.com/read/155551/5620757
asm start.asm
;/****************************************************************
;KPIT Cummins Infosystems Ltd, Pune, India. - 4th September 2003.
;
;This program is distributed in the hope that it will be usefu
www.eeworm.com/read/154801/5634331
asm start.asm
;/****************************************************************
;KPIT Cummins Infosystems Ltd, Pune, India. - 4th September 2003.
;
;This program is distributed in the hope that it will be usefu
www.eeworm.com/read/293183/8310268
m bpxnc.m
%BPXNC Neural net classifier based on MATHWORK's trainbpx
%
% [W,R] = bpxnc(A,n,iter,Win,T,fid)
%
% A feedforward neural network classifier with length(n) hidden
% layers having n(i) neurons in la
www.eeworm.com/read/293183/8310593
m lmnc.m
%LMNC Levenberg-Marquardt neural net classifier
%
% [W,R] = lmnc(A,n,iter,Win,T,fid)
%
% A feedforward neural network classifier with length(n) hidden
% layer with n(i) units is computed for the d
www.eeworm.com/read/392443/8342000
m covsrt.m
function [covari] = covsrt(npc,ma,ia,mfit,covari)
%
% Expand in storage the covariance matrix covari, so as to take into
% account parameters that are being held fixed. (For the latter,
% return z
www.eeworm.com/read/413184/11163798
mch marks.mch
MACHINE Marks(mmax)
CONSTRAINTS mmax:NAT1
VARIABLES record
INVARIANT record : 0..mmax --> NAT
INITIALISATION record := {}
OPERATIONS
addmark(mm:NAT) =
www.eeworm.com/read/236978/13984694
c imvc07.c
/***************************************************************************************************
File Name : IMVC07.c
Project : IMVC position control on ACPM750 AC Power Mod
www.eeworm.com/read/289085/8577328
lst start.lst
_____________________________________________________________________________
F2MC-16 Family SOFTUNE Assembler V30L11 2007-03-02 13:17:36 Page: 1
- ASSEMBLE INFORMATION - ( STARTUP )
|
www.eeworm.com/read/386050/8767263
m ffnc.m
%FFNC Feed-forward neural net classifier back-end
%
% [W,HIST] = FFNC (ALG,A,UNITS,ITER,W_INI,T,FID)
%
% INPUT
% ALG Training algorithm: 'bpxnc' for back-propagation (default), 'lmnc'
%
www.eeworm.com/read/386050/8767485
m kmeans.m
%KMEANS k-means clustering
%
% [LABELS,A] = KMEANS(A,K,MAXIT,INIT,FID)
%
% INPUT
% A Matrix or dataset
% K Number of clusters to be found (optional; default: 2)
% MAXIT maximum numb