代码搜索：evaluate

找到约 3,619 项符合「evaluate」的源代码

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m visohhred.m

function niso = Visohhred(vv, iext); % VISOHHRED - computes n(V) for the dV/dt=0 isocline for the reduced (2 variable) HH % model. Uses fdvdt103 to evaluate dV/dt. iext must be a scalar. vv can be % a
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www.eeworm.com/read/379733/9179975

m feedback_taylor.m

function [dm, dv, dmv, dev] = ... feedback_taylor(dgm0, dgv0, dgmv, dgev, m_in, v_in, mv_in, ev_in, nonlin) % FEEDBACK_TAYLOR Evaluate the gradients of Taylor % approximation of nonlinearity [
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www.eeworm.com/read/182453/9203735

m eval_ar_perf.m

function [ypred, ll, mse] = eval_AR_perf(coef, C, y, model) % Evaluate the performance of an AR model. % % Inputs % coef(:,:,k,m) - coef. matrix to use for k steps back, model m % C(:,:,m) - cov
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www.eeworm.com/read/373627/9446221

html semat.html

R: Evaluate Kriging Standard Error of Prediction over a Grid
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www.eeworm.com/read/373249/9467872

m student_t_logprob.m

function L = log_student_pdf(X, mu, lambda, alpha) % LOG_STUDENT_PDF Evaluate the log of the multivariate student-t distribution at a point % L = log_student_pdf(X, mu, lambda, alpha) % % Each col
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www.eeworm.com/read/176166/9513591

cygwin makefile.cygwin

# $Id: Makefile.cygwin,v 1.7 2003/05/20 00:27:55 n8gray Exp $ CC=gcc AR=ar # For editres, add -DEDITRES to CFLAGS and -lXmu to LIBS # # To evaluate an alternative layout for the Replace/Find dialog,
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www.eeworm.com/read/176166/9513597

qnx makefile.qnx

# $Id: Makefile.qnx,v 1.3 2003/05/20 00:27:56 n8gray Exp $ # # Makefile for QNX # (reference: NEdit develop mailinglist) # CC=cc AR=ar # # To evaluate an alternative layout for the Replace/Find dial
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www.eeworm.com/read/164422/10108750

m student_t_logprob.m

function L = log_student_pdf(X, mu, lambda, alpha) % LOG_STUDENT_PDF Evaluate the log of the multivariate student-t distribution at a point % L = log_student_pdf(X, mu, lambda, alpha) % % Each column
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www.eeworm.com/read/164039/10134502

m eval_ar_perf.m

function [ypred, ll, mse] = eval_AR_perf(coef, C, y, model) % Evaluate the performance of an AR model. % % Inputs % coef(:,:,k,m) - coef. matrix to use for k steps back, model m % C(:,:,m) - cov
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www.eeworm.com/read/163776/10146003

m eval_ar_perf.m

function [ypred, ll, mse] = eval_AR_perf(coef, C, y, model) % Evaluate the performance of an AR model. % % Inputs % coef(:,:,k,m) - coef. matrix to use for k steps back, model m % C(:,:,m) - cov
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