代码搜索：Matrix
找到约 10,000 项符合「Matrix」的源代码
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www.eeworm.com/read/325790/13184900
m xlinear.m
function obj=xlinear(varargin)
% Holds a matrix which forms a linear expression.
%
% Syntax: (* = optional)
%
% obj = xlinear(expression, evalvar*, varsize*);
%
% In arguments:
%
% 1. express
www.eeworm.com/read/325790/13184920
m initgrad.m
function grad=initgrad(obj,diffvar)
% Generates a gradient with respect to the variable represented by the integer given in 'diffvar'
%
% Syntax: (* = optional)
%
% grad = initgrad(obj, diffvar);
www.eeworm.com/read/325790/13185244
m danl.m
function obj = pfsys(varargin)
% Constructor for the DANL (Discrete Additive Non-Linear) model
%
% x(t+T) = f(x,t) + gu(x,t)*u(t) + gw(x,t)*w(t)
% y(t) = h(x,t) + hu(x,t)*u(t) + e(t)
%
% Synta
www.eeworm.com/read/138798/13211557
m matprint.m
% MATPRINT - prints a matrix with specified format string
%
% Usage: matprint(a, fmt, fid)
%
% a - Matrix to be printed.
% fmt - C style format string to use for
www.eeworm.com/read/138798/13211950
m conffig.m
function fh=conffig(y, t)
%CONFFIG Display a confusion matrix.
%
% Description
% CONFFIG(Y, T) displays the confusion matrix and classification
% performance for the predictions mat{y} compared
www.eeworm.com/read/138798/13211988
m netgrad.m
function g = netgrad(w, net, x, t)
%NETGRAD Evaluate network error gradient for generic optimizers
%
% Description
%
% G = NETGRAD(W, NET, X, T) takes a weight vector W and a network data
% stru
www.eeworm.com/read/138798/13212373
m mlphess.m
function [h, hdata] = mlphess(net, x, t, hdata)
%MLPHESS Evaluate the Hessian matrix for a multi-layer perceptron network.
%
% Description
% H = MLPHESS(NET, X, T) takes an MLP network data struct
www.eeworm.com/read/138656/13226866
m sima1.m
function [nw,a1,i] = sima1(w,p,lr,rho,pf)
%SIMA1 ART1 simulation function.
% Each input vector is presented to the network one at a time.
% (See COMPET, HARDLIM)
%
% [NW,A1,
www.eeworm.com/read/240189/13232096
pro lin2d_fitxy.pro
; $Id: lin2d_fitxy.pro,v 1.2 2002/03/14 11:49:12 riccardi Exp $
;+
; NAME:
; LIN2D_FITXY
;
;
; PURPOSE:
; The procedure fits a 2-dim linear operator A described by the
; followin
www.eeworm.com/read/324303/13273659
m validate.m
function [cost,nmodel,output] = validate(model, Xtrain, Ytrain, Xtest, Ytest,estfct, trainfct, simfct)
% Validate a trained model on a fixed validation set
%
% >> cost = validate({X,Y,type,gam,sig2}