代码搜索：如何学习 cutoff？
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www.eeworm.com/read/428451/8867365
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/427586/8932255
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/426899/8992436
c coeff.c
/* Coeff.c: filter coefficient file */
/* *2.4 kbps MELP Proposed Federal Standard speech coder
*
*TMS320C5x assembly code
*
*version 1.0
*
*Copyright (c) 1998, Texas Instruments, Inc.
*
www.eeworm.com/read/282846/9056100
m threshold.m
function [out,flag] = threshold(inp,cutoff)
% THRESHOLD
% THRESHOLD(inp, cutoff)
% sets to cutoff any values in inp that are absolutely larger than
% cutoff
% inp is any matrix
% Matlab c
www.eeworm.com/read/183445/9158793
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/374698/9388966
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/176500/9495702
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/168454/9912397
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/166055/10038087
java graderange.java
//********************************************************************
// GradeRange.java Author: Lewis/Loftus
//
// Demonstrates the use of an array of String objects.
//*****************
www.eeworm.com/read/360895/10072735
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},