代码搜索：containing
找到约 10,000 项符合「containing」的源代码
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www.eeworm.com/read/365849/9844732
m hgradx_general.m
function v=hgradx_general(obj,x,t,u,varargin)
% Calculates: grad_x[h(x,t) + hu(x,t)*u(t) + e(t)]
%
% Syntax: (* = optional)
%
% grad_x = hgradx_general(model, x, t, u, e*);
%
% In arguments:
%
www.eeworm.com/read/365844/9844797
m std.m
function dev = std(chr)
% STD - Standard deviation
% For vectors, STD(chr) returns the standard
% deviation of the population. For matrices, STD(chr) is a column vector
% containing the
www.eeworm.com/read/365783/9847680
readme19
Chapter 19 - Programming for the Internet - HTML.
simple.html - a simple html document.
format.html - a document with text formatting.
lists.html - a document with unordered, numbered and d
www.eeworm.com/read/169560/9852307
vhd tb_a8237_top.vhd
-- Altera Microperipheral Reference Design Version 0802
--------------------------------------------------------
--
-- FILE NAME : tb_a8237_top.vhd
-
-- PROJECT : Altera a8237 DMA
--
www.eeworm.com/read/169469/9859924
m make_rp.m
% This file makes the structure containing the run
% parameters used for the Adpative Equalization experiment
rp.Nruns = 200;
rp.var_v = 0.001;
rp.decay = 0;
rp.p = 11;
www.eeworm.com/read/365309/9870049
vhd tb_a8237_top.vhd
-- Altera Microperipheral Reference Design Version 0802
--------------------------------------------------------
--
-- FILE NAME : tb_a8237_top.vhd
-
-- PROJECT : Altera a8237 DMA
--
www.eeworm.com/read/364264/9916751
m checkvarsdata.m
function [data,params]=checkvarsdata(start,continuing,data,params);
%CHECKVARSDATA Fills the dataset variable for the GPLAB algorithm.
% CHECKVARSDATA(START,CONTINUE,DATA,PARAMS) returns the da
www.eeworm.com/read/363803/9935716
m cp0901_muiber_2pam.m
%
% Function 9.4 : "cp0901_MUIBER_2PAM"
%
% Evaluates the theoretical probability of error
% for a 2PAM system in AWGN channels under the
% Standard Gaussian Approximation
%
% 'ebn0' is a v
www.eeworm.com/read/167735/9953586
m manhattan.m
function D = manhattan(X,z,W);
% manhattan : calculate a 1*n vector D containing manhattan distances from z
% to every vector in X
% D = manhattan(X,z,W)
% X - d*n matrix containing the ve
www.eeworm.com/read/167735/9953620
m loadiris.m
function [iris,irisc] = loadiris();
% LOADIRIS : loads the cluster IRIS benchmark data
% [iris,irisc] = loadiris()
% iris - a 4*150 matrix containing the 150 samples
% irisc - a 1*150 category vector