代码搜索：hopf
找到约 90 项符合「hopf」的源代码
代码结果 90
www.eeworm.com/read/381850/9068363
h hopf.h
/*----------------------------------------------------------------------
File : hopf.h
Contents: Hopfield network as associative memory
Author : Christian Borgelt
History : 2002.12.01 file
www.eeworm.com/read/381850/9068377
c hopf.c
/*----------------------------------------------------------------------
File : hopfield.c
Contents: Hopfield network as associative memory
Author : Christian Borgelt
History : 2002.12.01
www.eeworm.com/read/380747/9129821
m hopf.m
www.eeworm.com/read/169875/9835262
m hopf.m
www.eeworm.com/read/165165/10073804
m hopf.m
%Example 3.26
%
clf;
figure(gcf)
setfsize(300,300);
echo on
clc
% NewHOP - 设计Hopfield网络
% SIM - 对Hopfield网络进行仿真
pause % Strike any key to define the problem...
clc
T = [+1 +1;
www.eeworm.com/read/240954/13186257
m hopf.m
www.eeworm.com/read/223460/14641208
m hopf.m
www.eeworm.com/read/270548/11033331
m wiener_hopf.m
function outputWeights = wiener_hopf(stateCollectMat, teachCollectMat)
% computes ESN output weights from collected network states and collected
% teacher outputs. Mathematically this is a linear r
www.eeworm.com/read/239320/13288018
m hopf_jac.m
function [J,res]=hopf_jac(x,omega,v,par,free_par,c)
% function [J,res]=hopf_jac(x,omega,v,par,free_par,c)
% INPUT:
% x current Hopf solution guess in R^n
% omega current Hopf frequency guess in R
% v
www.eeworm.com/read/154673/11939223
m wiener_hopf.m
function [h,Yn,e2]=wiener(rxx,rdx,Xn)
% according to the equation h=inv(Rxx)*Rxd
% Yn=cov(Xn,h)
% E[e2]=Rxx(0)-cov(Rsx,h)
% Page 33