代码搜索：如何学习 cutoff？
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www.eeworm.com/read/479074/6698992
m plnumsat.m
function plnumsat (eph,tsat,elev,cutoff)
%PLNUMSAT: Plot number of satellites
%
% The function create a plot showing the number of satellites
% above the elevation cutoff as a fucntion of time
%
% Syn
www.eeworm.com/read/478412/6717484
m lsf.m
function LSF=LSF(Lambda, F, x)
% LSF(Wavelengths, Focal_Ratio, X-Coordinates)
%
% Computes the monochromatic diffraction-limited line spread function at
% the given wavelengths (rows) at the coord
www.eeworm.com/read/264747/11302929
m prog82.m
%
% Program 8.2, p511. m-file for the design of the
% impulse invariant filter (Example 8.19)
% program name: prog82.m
%
Fs=1000; % sampling frequency
fc=300; % cutoff frequency
WC
www.eeworm.com/read/154760/11929428
m ctfirstorderfilter.m
function [f, h] = ctfirstorderfilter(type, cutoff, bandwidth)
% CTFIRSTORDERFILTER implements continuous time filters, to be used with
% cltidemo.
% [f, h] = ctfirstorderfilter(type, cutoff, bandw
www.eeworm.com/read/255577/12072546
m f_tipsfir.m
% GUI module => g_fir
%
% User tips:
%
% 1. All changes to edit box parameters are activated with
% the Enter key.
%
% F_0 = lower cutoff frequency
% F_1 = upper cutoff frequ
www.eeworm.com/read/255577/12072797
asv f_tipsfir.asv
% GUI module => g_fir
%
% User tips:
%
% 1. All changes to edit box parameters are activated with
% the Enter key.
%
% F_0 = lower cutoff frequency
% F_1 = upper cutoff frequ
www.eeworm.com/read/150749/12267284
m sparselssvm.m
function [pmodel,nb,errest] = sparselssvm(model,tradeoff, step)
% Remove iteratively the least relevant support vectors in order to obtain sparsity
%
% >> selector = sparselssvm({X,Y,type,gam, sig2},
www.eeworm.com/read/150749/12267442
m sparselssvm.m
function [pmodel,nb,errest] = sparselssvm(model,tradeoff, step)
% Remove iteratively the least relevant support vectors in order to obtain sparsity
%
% >> selector = sparselssvm({X,Y,type,gam, sig2},
www.eeworm.com/read/119681/14824505
m sparselssvm.m
function [pmodel,nb,errest] = sparselssvm(model,tradeoff, step)
% Remove iteratively the least relevant support vectors in order to obtain sparsity
%
% >> selector = sparselssvm({X,Y,type,gam, sig2},
www.eeworm.com/read/214923/15083060
m sparselssvm.m
function [pmodel,nb,errest] = sparselssvm(model,tradeoff, step)
% Remove iteratively the least relevant support vectors in order to obtain sparsity
%
% >> selector = sparselssvm({X,Y,type,gam, sig2},