代码搜索:coefficient

找到约 3,200 项符合「coefficient」的源代码

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m binomial.m

function b = binomial(n,k) %BINOMIAL compute binomial coefficient % % Usage: b = binomial(n,k) % % Parameters: ( n ) % b = ( ) % ( k ) % % Author: Steve Gunn (sr
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m program_09_3.m

% Program 9_3 % Coefficient Quantization Effects on the % Frequency Response of a Direct Form FIR Filter % fpts = [0 0.5 0.55 1]; mag = [1 1 0 0]; b = remez(39,fpts,mag); [h,w] = freqz(b,1,512);
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m program_09_7.m

% Program 9_7 % Granular Limit Cycles in First-Order IIR Filter % clf; alpha = input('Type in the filter coefficient = '); yi = input('Type in the initial condition = '); x = input('Type in the
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m program_06_1.m

% Program 6_1 % Factorization of a Rational Transfer Function % format long num = input('Numerator coefficient vector = '); den = input('Denominator coefficient vector = '); [z,p,k] = tf2zp(num,
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m program_06_3.m

% Program 6_3 % Cascaded Lattice Realization of an % Allpass Transfer Function % format long den = input('Denominator coefficient vector = '); k = poly2rc(den); knew = fliplr(k); disp('The lat
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cpp rootnewtonhilldown.cpp

//RootNewtonHillDown.cpp //牛顿下山法求解代数方程全部根(实根和复根) #include //输入输出流头文件 #include "NonLinearEquation.h" //非线性方程(组)求解头文件 using namespace std; //名字空间 void main(void) { int i, i
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m exa050904_latcfilt.m

% ------------------------------------------------------------------------------ % exa050904_latcfilt.m , for example 5.9.4 %to test latcfilt.m and to realize filtering with LATTICE coefficient. %
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m copulastat.m

function tau = copulastat(type,param) %COPULASTAT Kendall's rank correlation for a copula. % TAU = COPULAPARAM('Gaussian',RHO) returns Kendall's rank correlation % TAU corresponding to a Gaussi
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m copulaparam.m

function param = copulaparam(type,tau) %COPULAPARAM Copula parameter, given Kendall's rank correlation. % RHO = COPULAPARAM('Gaussian',TAU) returns the linear correlation % parameter RHO corres
www.eeworm.com/read/165079/10077436

m dominantpass.m

function [D,X,sublist] = dominantpass(X,threshold,sublist) % Dominant pass function D=[]; global N; [m,n]=size(X); % X is the coefficients matrix R=zeros(m); % matrix R is a reference