代码搜索：optional
找到约 6,947 项符合「optional」的源代码
代码结果 6,947
www.eeworm.com/read/433250/8537485
m ptfddb.m
function ptfddb(tfd, dbs, t, f, fs)
% ptfddb -- Display an image plot of a TFD with a dB amplitude scale.
%
% Usage
% ptfddb(tfd, dbs, t, f, fs)
%
% Inputs
% tfd time-frequency distribution
%
www.eeworm.com/read/433250/8537490
m fmsin.m
function x = fmsin(N, p, phs)
% fmsin -- create a signal with a sinusoidal frequency modulation
%
% Usage
% x = fmsin(N, p, phs)
%
% Inputs
% N length of the signal
% p number of cycl
www.eeworm.com/read/433250/8537548
m choi_williams1.m
function [tfd, t, f] = choi_williams1(x, fs, sigma)
% choi_williams1 -- Compute samples of the (type I) Choi_Williams distribution.
%
% Usage
% [tfd, t, f] = choi_williams1(x, fs, sigma)
%
% Inpu
www.eeworm.com/read/433250/8537625
m ptfd.m
function ptfd(tfd, t, f, fs)
% ptfd -- Display an image plot of a TFD with a linear amplitude scale.
%
% Usage
% ptfd(tfd, t, f, fs)
%
% Inputs
% tfd time-frequency distribution
% t vec
www.eeworm.com/read/433250/8537633
m choi_williams1.m
function [tfd, t, f] = choi_williams1(x, fs, sigma)
% choi_williams1 -- Compute samples of the (type I) Choi_Williams distribution.
%
% Usage
% [tfd, t, f] = choi_williams1(x, fs, sigma)
%
% Inpu
www.eeworm.com/read/433250/8537677
m ptfddb.m
function ptfddb(tfd, dbs, t, f, fs)
% ptfddb -- Display an image plot of a TFD with a dB amplitude scale.
%
% Usage
% ptfddb(tfd, dbs, t, f, fs)
%
% Inputs
% tfd time-frequency distribution
%
www.eeworm.com/read/433250/8537685
m fmsin.m
function x = fmsin(N, p, phs)
% fmsin -- create a signal with a sinusoidal frequency modulation
%
% Usage
% x = fmsin(N, p, phs)
%
% Inputs
% N length of the signal
% p number of cycl
www.eeworm.com/read/287962/8656475
txt wml教程6：动作和链接.txt
作者：蓝
email: lanxk@263.net
日期：00-6-17 下午 12:46:48
设置动作（Do）
Do是WML语言中最有有价值的元素之一，它给用户提供一种在当前Card上进行"动作"的通用方法。这种动作通常被定位在用户终端界面的特定部件上，例如WAP手机的功能键（Cancel，Option，Accept），特定的图标，语音识别功能等等。Do可以设置在Deck的Templa ...
www.eeworm.com/read/431675/8662377
m learnbpm.m
function [dw,db] = learnbpm(p,d,lr,mc,dw,db)
%LEARNBPM Backpropagation learning rule with momentum.
%
% [dW,dB] = LEARNBPM(P,D,LR,MC,dW,dB)
% P - RxQ matrix of input vectors.
% D - SxQ matrix o
www.eeworm.com/read/386050/8767532
m pinvr.m
%PINVR PSEUDO-INVERSE REGRESSION (PCR)
%
% [W,J,C] = PINVR(A,TYPE,PAR,C,SVR_TYPE,EPS_TOL,MC,PD)
%
% INPUT
% A Dataset
% TYPE Type of the kernel (optional; default: 'p')
% PAR Kernel par