代码搜索：initialisation
找到约 2,024 项符合「initialisation」的源代码
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www.eeworm.com/read/278391/10538479
lst start.lst
_____________________________________________________________________________
F2MC-16 Family SOFTUNE Assembler V30L11 2008-01-06 16:22:06 Page: 1
- ASSEMBLE INFORMATION - ( STARTUP )
|
www.eeworm.com/read/436309/7772759
txt readme.txt
POSIT Version 1.00 - source codes of multitasking OS for PIC microcontroller
Copyright (c) 1998 Pavel Baranov (pbaranov@spb.lucent.com)
Postcardware:
-------------
These source codes are distr
www.eeworm.com/read/140836/13059841
txt readme.txt
POSIT Version 1.00 - source codes of multitasking OS for PIC microcontroller
Copyright (c) 1998 Pavel Baranov (pbaranov@spb.lucent.com)
Postcardware:
-------------
These source codes are distr
www.eeworm.com/read/138357/5816689
gnokiirc sample.gnokiirc
# This is a sample ~/.gnokiirc file. Copy it into your
# home directory and name it .gnokiirc.
#
[global]
# Set port to the physical serial port used to connect to your phone
port = /dev/ttyS0
# S
www.eeworm.com/read/155638/11858452
txt readme.txt
POSIT Version 1.00 - source codes of multitasking OS for PIC microcontroller
Copyright (c) 2004 Pavel Baranov (pbaranov@spb.lucent.com)
Postcardware:
-------------
These source codes are distr
www.eeworm.com/read/119799/14821123
s startrom.s
TTL Generic ARM start-of-day (initialisation) code > startrom.s
; ---------------------------------------------------------------------
; This file provides the Angel i
www.eeworm.com/read/431675/8662297
m emclust.m
%EMCLUST Expectation - Maximization clustering
%
% [D,V] = emclust(A,W,n)
%
% The untrained classifier W is used to update an initially labelled
% dataset A by the following two steps:
% 1. train W by
www.eeworm.com/read/418695/10935620
m emclust.m
%EMCLUST Expectation - Maximization clustering
%
% [D,V] = emclust(A,W,n)
%
% The untrained classifier W is used to update an initially labelled
% dataset A by the following two steps:
% 1. train W by
www.eeworm.com/read/444592/7611193
m ukfdemo.m
%
% Unscented Kalman Filter (UKF)
%
clear all;
clc;
echo off;
% INITIALISATION AND PARAMETERS:
% ==============================
sigma = 1e-5; % Variance of the Gaussia
www.eeworm.com/read/397102/8068531
m emclust.m
%EMCLUST Expectation - Maximization clustering
%
% [D,V] = emclust(A,W,n)
%
% The untrained classifier W is used to update an initially labelled
% dataset A by the following two steps:
% 1. train W by