代码搜索：NetWork

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热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/179705/9341926

changelog

2005-05-21 Brian Gough * Makefile.am (pkginclude_HEADERS): removed unused file gsl_block_complex.h 2004-06-03 Brian Gough * gsl_check_ra
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www.eeworm.com/read/179705/9342506

changelog

2005-04-05 Brian Gough * blas.c (gsl_blas_ssyrk): test conformance against size correctly allowing for transpose 2004-12-21 Brian Gough
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www.eeworm.com/read/179705/9343433

changelog

2003-02-17 Brian Gough * canonical.c (gsl_permutation_canonical_to_linear): fixed bug confusing input and output (swapped pp and qq) Sat Apr 6 19:08:40 2002 Brian Go
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www.eeworm.com/read/179705/9343646

changelog

Mon Apr 23 10:31:58 2001 Brian Gough * unified error handling conventions to _e for error handling functions and no suffix for plain functions, so _impl functions ar
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www.eeworm.com/read/179705/9343736

changelog

2005-09-09 Brian Gough * min.h: improved error message, function can be discontinuous despite what error message said. 2005-04-28 Brian Gough
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www.eeworm.com/read/179705/9344326

changelog

2003-01-01 Brian Gough * gsl_matrix_complex_float.h (gsl_matrix_complex_float_get): removed const from zero * matrix_source.c (FUNCTION): removed const from z
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www.eeworm.com/read/374010/9423715

m drawnet.m

function []=drawnet(w1,w2,CancelVal,instr,outstr) % DRAWNET % ------- % Draws a two layer feedforward neural network. % % drawnet(W1,W2,CancelVal,instring,outstring) draws the
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www.eeworm.com/read/177674/9442421

m rbfunpak.m

function net = rbfunpak(net, w) %RBFUNPAK Separates a vector of RBF weights into its components. % % Description % NET = RBFUNPAK(NET, W) takes an RBF network data structure NET and a % weight vector
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www.eeworm.com/read/177674/9442598

m glmunpak.m

function net = glmunpak(net, w) %GLMUNPAK Separates weights vector into weight and bias matrices. % % Description % NET = GLMUNPAK(NET, W) takes a glm network data structure NET and a % weight vecto
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www.eeworm.com/read/177674/9442631

m mlptrain.m

function [net, error] = mlptrain(net, x, t, its); %MLPTRAIN Utility to train an MLP network for demtrain % % Description % % [NET, ERROR] = MLPTRAIN(NET, X, T, ITS) trains a network data % structure N
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