代码搜索：Approximation

找到约 1,542 项符合「Approximation」的源代码

代码结果 1,542
热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/412853/11180556

m fsfind.m

function [Fn,nwo,f,t]=fsfind(fun,T,N,P) %FSFIND Find Fourier Series Approximation. % Fn=FSFIND(FUN,T,N) computes the Complex Exponential % Fourier Series of a signal described by the function 'FUN'. %
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www.eeworm.com/read/411674/11233835

m greedyappx.m

function [sel_inx,Alpha,Z,kercnt,MsErr,MaxErr]=... greedyappx(X,ker,arg,m,p,mserr,maxerr,verb) % GREEDYAPPX Kernel greedy data approximation. % % Synopsis: % [inx,Alpha,kercnt,mserr,maxerr]=... %
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www.eeworm.com/read/300728/13895795

m fsfind.m

function [Fn,nwo,f,t]=fsfind(fun,T,N,P) %FSFIND Find Fourier Series Approximation. % Fn=FSFIND(FUN,T,N) computes the Complex Exponential % Fourier Series of a signal described by the function 'FUN'. %
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www.eeworm.com/read/203215/15363904

vhd r2p_post.vhd

-- -- post.vhd -- -- Cordic post-processing block -- -- Compensate cordic algorithm K-factor; divide Radius by 1.6467, or multiply by 0.60725. -- Approximation: Ra = Ri/2 + Ri/8 - Ri/64 - Ri/512 --
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www.eeworm.com/read/101204/15841756

m fsfind.m

function [Fn,nwo,f,t]=fsfind(fun,T,N,P) %FSFIND Find Fourier Series Approximation. % Fn=FSFIND(FUN,T,N) computes the Complex Exponential % Fourier Series of a signal described by the function 'FUN'. %
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www.eeworm.com/read/390840/8438010

m nnd11fa.m

function nnd11fa(cmd,arg1) % NND11FA Function approximation demonstration. % This demonstration requires the Neural Network Toolbox. % Copyright 1994-2002 PWS Publishing Company and The MathWorks
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www.eeworm.com/read/366144/9828564

di test7.di

Thu Sep 02 18:10:55 Eastern Daylight Time 1999 -----> # QMG test 7 - a circle with two elliptic holes and a crack. Thu Sep 02 18:10:55 Eastern Daylight Time 1999 -----> # Make an approximation
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www.eeworm.com/read/361798/10035454

m nene.m

function [s,V] = nene(z,rho,theta) % function NENE.M % Nearest neighbor approximation algorithm % [s,V] = nene(z,rho,theta) % z = M by N matrix with samples in frequency domain % rho, theta = radius
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www.eeworm.com/read/349111/10848967

m mwtlsr.m

function [M,dh] = mwtlsr(d,w,r) % MWTLSR - Weighted Total Least Squares misfit computation. % [M,DH] = MWTLSR(D,W,R) gives the WTLS misfit M and the WTLS % approximation DH of the data D by the model
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www.eeworm.com/read/349111/10848973

m mwtlsp.m

function [M,dh] = mwtlsp(d,w,p) % MWTLSP - Weighted Total Least Squares misfit computation. % [M,DH] = MWTLSP(D,W,P) gives the WTLS misfit M and the WTLS % approximation DH of the data D by the model
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