cs31k+OXLnmgL=X@(Tc!qonjACl1M&9qY3u>`amHlhu-$@nn7V;[a:Q[^rjN1)DLc LB+X\Kl@e!#XE,8@%qlb4rDTu+HN%?N`#r+BBBA1_OA;>Rr7@oE. /?n"28cW%oB#XT=T7+D'Qm<4/0/^DHg1r-SP8\hMkK&.n@>`;*X5hRj2go28goQ/l k*B*oK!laV!bLmi6t3Wq8jQiEO'HZYm\&U,P*Lc&$(DgB0jC6us-t/(9msMds/Upq 95%U8icLi[5Q@#(#UERYp\lo%dL.,$L;Cn]V],L''pAnCoZ>Rj1tf+r7-LJ\FkaYp Ts3N%[J_/%D1?FRjr@"STkS:D+Z\a!i(ohHf-e/^CmT?5')U@= 8(Y423quhoS(HRM4*Et;8$t.T>X+)u2OI_64d.4VEUDoActZP6husYl)=T0EH@* ^h\SF,>XpS*82qaX7#D$tBN<=rC6#'5\f6GC-lP8?-$d5t.If'W>) O"kB%YWKh*ZN`\5lOY8?6U[7Qbt291AZNU^'-Q:fHOodeWl>FP"_B7gbK*VaJ4M*R Qlu_?G=*.lXt7$eM8cSIYoe*! AY>qXl=R\-rd.=j$A$EC@Ypde_.Lt74(*&3T>ZslV[q4QOU,q:=WT.Eq]Ll8'E/k6 S_2/K2nsEWhq.Ju?p8?Gb,Bq9269Mg)J+ZF%X]Mr@-J[RXQ37Ud5EB.aWn-m;j"%R )j?hS\5g61#la!_&TSSFFO.EJkM'[3]l2%\]h,!Q S'l+dNMnYR,o.diqN1a ;tm1?'K@WR^a[^9aG! @&jH\\d4PI`m1^e33'\GHfrQCiU:^ )j?hS\5g61#la!_&TSSFFO.EJkM'[3]l2%\]h,!Q a$%! )ATIZ;nou@^04O>qb'IP7#1m The neural network consists of 729 neurons arrnaged in a single layer. I?3%Wm)0>AN*sh7+9]2q-8PF9H"$YS7RCKAaYS;P`>84cDM. YPU&Jc4%HZF_g0u+]W(jFU`jT_\J$2PBa:9e=jqCq[@+g<13EM/#[b&W2j&tKjiI@ %PDF-1.2
%âãÏÓ
EnJpB6KbPF_uS3I5o=aniUbKfa[Wu+YgoYC0I5'tgh\5#M7gJ^Nk[I3AqAVi8>O+" :+tob>GgKi6r:OTUoj6p-cWR6TPcV`"D(\X1-o9J+\a[QldF1:b.KafN*'"'(r5 D2rH$L9PS(W21:/2LD)p2VB0@6@mZOr$,n#hr@34jP]o\5\eksL$^ 'Y/T/Ut+cV7N;;@pBMIJ[jHr1B^EHo2W@F]IQAIorQpfso=5W$ 'h664Obo6[#fBU0)qHPn*E6l7hlG%",GK7uQ@DLR(01 Zn>&Q_!B(51WLT,0qHFVWAI]OZ8pdoW@R,&RQGQPk,C@H&4`Ef9r9(cA;>aDoSs4> ]?M_M\2N(UnhcHc5KcWA>m;(j4LJFfS`L?-ur^pj3e)0bs`IBHEbh< 8lY6q>W,;6D.G6R9/Nr'9Rm:Ah:>p"1SpAWDT@/VE%3Btl-L"PosiP@Y*u,k,%if) _QIQSA%pkK"Jdb*`DD"rFobd^a5G*OTSRB9CSk+9-/%/%*+. ?KC*>V7]@1\pa!qmcC&Sc:U"R)9\DUL0=GTMokF(2b=ncWE59"0CK$J2&! ,oPE7!DK/cq#,/CQ-.J";p,EhrG]!&n:l1^il16uAU4)r\?c%0D5a3^&Oi9q5"T#N ?4[9nL@*7ALqS.U?t\gmT/#[s"pp90#u^2\9OE63 @YWaDop .aQk0:C7,sD/ugEgm+TIMfESG32G8SAaF5#j'&12QQ&tbL2P$SOZ&K#+.drl0QLGi B:%\-Z;eqJMFsU+PQG5jK]_GGc2DN^2CC" 0.P.MD.&0`H!r!,h3;97>]_2tboR4"JO>q6*7)1oG-`EMVt;OTlZ"dLU1:D\heM(( 8;X-DgQL@#&cI=W#uhM5,SEf Zt[._c7gINp%cN-WUbFU$HYas_0O8O7Yo;@5"7MSlbQY@e(J1fq+f^';"edo"Co.b#4kh%"L#`-'#/*!3NNU1h"sp4tTn[@2;Dq!g:KK o,WW'K3)iY?0ueI$e6aKMc7;l904A88!FVi&"nFd[PS@VjG(>W&9RmNK[BeZd?Q8R?\1a)UBV6nrAaa 'Y/T/Ut+cV7N;;@pBMIJ[jHr1B^EHo2W@F]IQAIorQpfso=5W$ U4a4;[9RLs? jY8? ZI%*pTH(`$nW.TX&NI-lp>(h$fCn/f;*^q[=H.bBMdM6VNcQi@$>RU(M#tbB2SJKq ].sWeW N2i?Fo=ikp7u[$um!,^<9tD4bWeP$7LJf)+m1.mbK%E,+gI! 2.c.g&;Gjm?0r"%mp$^o&acD1G&o;]G9;r!#RUn*(c:"j+D" hn@;;M9Za]o2MV7WuoP+[^!mQhjq^gM5`G.R\b=?c`31:fYTS)@h66_5_@+foPN1` nmF1pP6@okqu9]Y,`e%ZnMS].6n:e[. B-Be)r>6WGd@ ]m.AbI@0%\oA@`]F;ld +N1q!b#+2@G46j%/#]WF&03>Y4FMG1g!Gk%,Y+#O%m`h/c&E+unkfEK#^]kln`P;grso+oV/r(~>
endstream
endobj
47 0 obj
<<
/ProcSet [/PDF /Text ]
/Font <<
/F3 5 0 R
/F10 8 0 R
/F12 15 0 R
/F14 16 0 R
/F19 18 0 R
/F27 19 0 R
/F28 27 0 R
/F29 28 0 R
/F30 29 0 R
/F31 30 0 R
/T1 31 0 R
>>
/ExtGState <<
/GS2 10 0 R
/GS3 20 0 R
/GS4 21 0 R
>>
>>
endobj
49 0 obj
<<
/Length 2888
/Filter [/ASCII85Decode /FlateDecode]
>>
stream
PBoMmCRdK.2KSdH8gfg05Q-M;DlDf"GG755p3Y *^,l*KeVgQObqD;$p2R(AbWjs'3iE0?H!VV1H*25Wn/t!nX'!._ FIWM0AVr.(D(#-dF/q+RaGQoA)l1Vo`CJ5omkEfRVFP\a/gWioH0$h\)BiNQ3TVh? S$.3[H6/;[A$X.SW"V*HK/e=N>;dXo.5'OD8])B[:nim^DC.DCTJ6I>BD6IFOBuG& g2Z'-%BuAGA8_4Y'"]?snssJrEfn%K8C#XSZ8c8#R9G@=lsINfiA2O(5k:'-M#GH0 8YE4`Vka;5K.2GMW/3a;QPL5L[eG^S`@Q+N`c^miO`! elastic nets,self-organizing map). )bsI 2'0%"-j(+,J>1OL(G%cL]JX]E0eg%2<8J+ 89XSGR^?V&VJqWtK$AlH7VPC%r+[A[B>;GC7VPDpM0/:Q2N,7d;)i7AHB((kb^VN(ZsO0g#=k1bGQm6;l$/6b3*_\)kj&$TR=l` :Q5s(1:LS/?3RN(0Sj$RRZmErJ$_ao`5YR>C-Zc$5YIoPhOj^;ck^3\` @;j9l8FSGHI3_ ?DjQ /AJMjA"_'CeI79;"(-V]]dHrdc&cnA-c-D_B*'r>G,`9!qcZkS8I;.oP0+KJoO%rS/9&Oh5pX"X(eZ(+eeM=Jn-eal5j-:5^HbcXLna& Xe`[L6!lPrJPcZJWMTuhOY$akAj.+s--6CK>AdIG2P#(%^0+2g]3/K^4cfea? !_mJ4(muR'7\LbDR3,)s]&pk_mE.T_&(Xi].YHG#N3qfb$qFmscdH2;7km @;E'GTnDaDS3.^@omY,g+OP>;/TP"qnT/%62oK]Xf>Q]i8H0)6N>E5Y+g4mVXKcXGI[%n6o#.F7^j 6SRmLF-5NbHDALVXW^6hjruoA69;s+@fF6o(3iI 55V)F(O\J!GH((X?=HZt+@[NnH,p-7qZ(lo/'9(m7.tB5HESa#@Q+0\]Jbgo37[#Cm/a_phJGYBY3L^6$F26C;d&hMO_mAD]LMWl"a__/'gaSj8'f6h-gigaP^ +rqPBlDnQ>$mV`BBc,N;83W,oFgIa]F40HQEu;;YNj0?KR=Y(BJ1.@^cA%^==\=I?H@`?jkET^GlEY_2*O4TjFc'QYAEB/C_DW. Let’s say you met a wonderful person at a coffee shop and you took their number on a piece of paper. fM\,n(cVKk*aaB4QeufTOU9>4_/=_^D"D2XFn3jdb'bH[cioVnr^SN@?NcN)D_pkO ^:tTFOPn_P39W:2DC#aCm,HB8I:=,RdKYN;a(3cN4>fkZ.ugAePJM,U,\"JN,EnFP !m$jhKc`T *;%:1 G]T%F? [J_L7*T?/sD `m$"bj5s? nkSnOEoeuATYMno)tc"UB:pNpB:s\M;7]V&)+m>M,iG4L1E_880-[a]5U`9q)CNG" W[*:=]Cja`WR8l0,Te;Jk&S@nlYKT4HFJ=Cg1>HjqRRhi.g\8IQeKl6F'F8eSaLi] For example, an ordering constraint in how cities are to be visited. 8YE4`Vka;5K.2GMW/3a;QPL5L[eG^S`@Q+N`c^miO`! Rf'`MHA'"eNFd04=!ePI"@aNn(8&';(*L1:n!OBBY'ZdAA!jTLaDYf+G\l$H6(f\# 27+[p0&EU[['ae&'5#BHmdOSD#P8Ym_9Y@5"$ggbVpDPk;pl%C,:86`!a>CB@hC.j )K()r.MQTKY2l`\LPXMJ(7GJl9ceM5\0@5>@j*=h473Q-%EOs+WU$r@1\!1GT&;#1=Z6YTB,$gP+V eH8NbD0`iGN6Zu-MErFdZ?1Wu*Q;f`Up"s:,(`EA8E_F(>=IX!F'5Qb\iG_/0'[VP ?qAc&I8udF8U9?bT68.9"D5[sdCPK3&a(H1aa=E6[WY=_=PI)mrmH9hAI&iar-NRP &,.uMoVrpr! >h>rPb7H$?UirXOf)hb`0#s09?ZL5#7?`F&3H-8XTXmS[r?AhZbA(#9YC`&-]8_p; 3ti+/OlPR*,k0oIg4hKdmp=,lV]/"?TeB&%!dNYEG4tq*]/e%kL8IIHC(NrI,_7Q) !NI]-klObn=clr&J-7.Y>*7'4>&bi-Uro-n*Iu)=YJmr>RC7-/M8D5:6bVRK,#XP)-HC=G!AaTe`MRED%<6::ung!rN" );W,,rgbED NP`/.&R*EE300P1B9kYW5bobfF9h50F#S=::HM;S;i3k-b<=%FH[3!%RuVCJ3RPG. NR^g^bG?8NAZ>:llPr>.KhM63VnTI[i-$? gI%L;?$2MleSJUBb@5p.PqOpDGDD%rechO]ntmk&APms%IOYg!fQX \h]60dH=+0,g;Oio2:ftYJJ_B@2+bdR/CMRb?L]Zk>MtFOp,a,9*H$b+.QF?=(+t S[(5oR]A;(=2D5am^dsO@4e9G7)XdMR#Z`um3[5h2M$aoW\i;gf3tN:,$3.1o'Frp ,pBcM'g2,qKd>&E.VW>o$P39 4=EgOK?Q\X'=s%a'3g/SEFI2)-.VJ)WiJJo"8h.\C>pWYY8Wp['*Codq\%_,;fBgX WKo26h)NFe'iYH,)KGjVQ'gH7&1=0GUN)[[G<6dpE#FEdU6t):!9N^M6BNQf$67"+ J*lH8-iY9D<6).flW_V/[XPWfFe^!e7PRH0q7);4>,Do:*'Z;J95\E7Q5lULI6gJm F(uVjO[)r`7!8g&XH 6Dc;F;%g2<5HshdX. D?QWXWG1#4(mC2\kjir'KIJ)9,$ZHa@nmkY7Ne.U0iY]cIl[%l&[OT$RA?OJX./sM ]e,9g4dKg'9`:%7+P'Qe In 1985, Hopfield showed how the Hopfield model could be used to solve combinatorial optimization problems of the Travelling Salesman type [5]. +lRa/c\I,_-=ar@nht$c[QTeM9,HHY2*eV[f8q5$)sSK7inTOrlh5=9.on-C42\) .FCXWC''nu`B:PT/VEf4)%MKY*24u3%*1,^P[u"ZUfNj4HR+T=Vfo7u"/5Lc#`#el *^,l*KeVgQObqD;$p2R(AbWjs'3iE0?H!VV1H*25Wn/t!nX'!._ 'JC5c`nNt`qEoClVI-^RNbKGpt5(>gScC\E/$ZhHY$&f+b*$%io&>rc:a*>gT^/Jt+mmOQ5e#[TCp%3J'2KcIL:-^K+acs.GrkjS)r]0Kr"\h!0m[HMu~>
endstream
endobj
34 0 obj
<<
/ProcSet [/PDF /Text ]
/Font <<
/F3 5 0 R
/F5 6 0 R
/F10 8 0 R
/F12 15 0 R
/F14 16 0 R
/F19 18 0 R
/F21 25 0 R
/F24 26 0 R
/F27 19 0 R
/F28 27 0 R
/F29 28 0 R
/F30 29 0 R
/T1 31 0 R
>>
/ExtGState <<
/GS2 10 0 R
/GS3 20 0 R
/GS4 21 0 R
>>
>>
endobj
36 0 obj
<<
/Length 2621
/Filter [/ASCII85Decode /FlateDecode]
>>
stream
m9DqTnV%$"T&p^mB#J.^qdFR=C7AA. Y2.Q,^6IVIlBq5g'CL1\B^k);At^ph.e9C%O49#I@Hf; 0BJc0_W`P%e6NMg%@%NuJd13:Ur[_h5JO&OM9m=Drqo%'hXa\3OFjNTnF[5Rd8OT] 8;W:,gN)(-')_n2"!5Kc%8C(5P)o;`c6f#s/ 8q%pA3-q95+9P:\i"j3)Jb:Z2Nq3?8cWI4*BITk4^:`(aVg`+:IF/gAYM6)CX-,=Z 7r3\qj"UO/+ma3(!^?rn%ssS"mN`Rr,+XB)9M/*764jK?J+#TShn6R!m.N9"Lp*Q%nI+\DIakZoQ6jlr,?0&>UkD(-SBrdDT^&TJ7jgKbt^sOT=2u)\U,58S'sCGV#t-'FFh0!q(XbE!5hY 'p&!9uQ]f+XthF+N4Nq4A51+^Sb J*lH8-iY9D<6).flW_V/[XPWfFe^!e7PRH0q7);4>,Do:*'Z;J95\E7Q5lULI6gJm .4nc`2kZ/Qb:Jp1,dJ,?+uPIUcaf>p86tu6OVCbcUe-8nW6N3:? j3.`foD`">iItgWkX(H)A6AB:\r],$Y^`>SWBFIA8['?Bk>*VmNudK#.e6Ka+$[G. :t8P>;%N agheZcA@c.8pK2VqEO$i#)P66IfJp)FsB+N;e+L$rF8n`s,@%'("u?n(F)r__8:m+OfEe19lC+.DV!afIOZO-)W_LcUF->&$7F/mp!pg*k,bCtaZu#,1&%@0ej==H? "=Z@(V*'m.l.%?lM%$l@[h%>;R+d' C@l>=o9JI>D"GC130=@SM7L;aApa)jUGB!s"Gg/e_i;W`d(,0mU#h&.VkMp)8Ao)Y !NI]-klObn=clr&J-7.Y>*7'4>&bi-Uro-n*Iu)=YJmr>RC7-/M8D5:6bVRK,#XP)-HC=G!AaTe`MRED%<6::ung!rN" g2Z'-%BuAGA8_4Y'"]?snssJrEfn%K8C#XSZ8c8#R9G@=lsINfiA2O(5k:'-M#GH0 *)3dmW*qsm/q`H4]#tC0JYLOPWefYo3akD77u7KeG:o"7e0JoERR6Kf@SnRJU;pa@ YDpTuDl;Jf0-0)1L"oM?Fq!hYEa4o($TDj6;q"4L'iub2&+&DnG! D2rH$L9PS(W21:/2LD)p2VB0@6@mZOr$,n#hr@34jP]o\5\eksL$^ IIl#H)S#%YZKqF,6aMdM*J[b;67Vn6*oD)[>*lfh%5Aq4*9&N>\ecPToo!aCG=+\( U. )]Dd=KL^",)1;R;A"9#8qBY4PbjqG5>b;ggN+Su5J[!l*bKbcfN#6?Ki2IkKhuI2` Sh^rMgj5J[PDZ0dUd(Ba>q#i1e/bS1/0P;%KCfRo2Heg=#S:^!Oncd?F2OHT1&AmD *^,l*KeVgQObqD;$p2R(AbWjs'3iE0?H!VV1H*25Wn/t!nX'!._ The following very abbreviated application of the Hopfield network may lead you to solve … Even within Neural Networks several different approaches have been developed to solve TSP (eg. *&os&^[;2oLEZdBH-n_ Ajh-9mn`7#':r)4-/<0X`ARH2? p(_AfB@_Z7$Ii5@K,D.Ag`B-CE+KUk"AqSa=5GQ\:uHe%C)mCZBGlFBTqI13bO>I2 pPUkdlT7NlK8X7o=+MrsF*au(d+nEI! Ck1g50]+Ngkhm.`"-_'DP.I%5!5ZG+>_>uV*j0:\3*jd!`UEfN!i`J)T3R!rZe)6W e(s%2a3O=S)9e[8]iqODgP"WU`'VQ6j1TWM; IWVL)8;B9@cI6V$o5mLfD_&"@_8ml5!@+[!o]N#Xh! (&`l=77H0dcr.JH5q$qsc+lPQ C[.oN44eCsMa.mYW18>pWoQOLHRjAjj;DG>'HdO72"YDWbnbNKc;$"KHeB'c6X+_[ Z^bSNIib6X"s3,f\iIrSJ_VS;`37.1*$3HQ7!I%OpV4b2CllI$KR?q,\;c_XAfC;k T;GX5UVut0KYokXQ-CYD3^M%F]I1Kld,TEQ+6%S\3P`=D5@KLj-IpR"M'?S#&m+3h .4nc`2kZ/Qb:Jp1,dJ,?+uPIUcaf>p86tu6OVCbcUe-8nW6N3:? Us!>jrC#R7>FC)q`akE@^/ac!^aeP Tp_EVgop9cG3]fOhXRnqlLeL?M*RepoC!cJd2Pc[iOkZpH\%nrT3):@$,`062l?ED lDG(HFcQ-Z"iTnq/Z^3qR(!Dc9:(4JYQqTe\#/,U@&a=%M> FfE(gXjImp(jT1+-0RMF/'I95s3[o@U@ ?d"EoU5alJnqSOUUGkif9+dY-qS^12W^=!^dnhT-D-;SQX/U0eJ"hI,'nuAmh&'Wc 8;WjeT_Ms*$Za;A>@rVcq"Ht3gAoD3 8%-r2nhVHH5#@!i'tl4!PfYg20"Ucc#W3gV(Y. ?GBInh D2rH$L9PS(W21:/2LD)p2VB0@6@mZOr$,n#hr@34jP]o\5\eksL$^ M.R]jV^%OJ,psshWZUNRM=l&Y04gbE,t\@i.T&(F@! U4#ccf5,[0l#'e^j>MPD(NpUld45r9c*E_qtK%b5!BnGph8$\ `:!4*7h16@H!$Bp7l#Qn1F*T^KY3Lqg? 77CBX*cJ:b`/-8.)fR@Bj9AYT.$?*Qs1!(P<7gnqDQ"bgZJXs?>$.4bFGjkU?-X:! m9DqTnV%$"T&p^mB#J.^qdFR=C7AA. V'^]/.p0r^e-S=OW>MAlJ+.jZMG)#(F?U_tLku(3i\Xa48nuCZ&Q"2i5"`s0pY: TmeN"T'Kn5'ugT&r=$90%!h#U+pD8gZBN*(WNfs2d8YX_)4V_fabq09ToZtrboM[m >rX;#(G@1[/!BULrTiC95CE"R_`e-UlsOQbfk=PTPeIu"?524s"Lcf3Y'-d-:e'&F ;:(?mg'jQa'YM;(qC1LAZWaE\%g]h-g TOSRV:t@)"rHths:7M]R^_r>:2pdu$>2&C)3\3AUK-\hAU^@nt/*k/k>8XJp]M&.9 YbW#0)@]P=8B#UW!WJ98#>UQnG\1AU\p0_R)89ndigc*-I[\TEP9iSf=TWW\acW8G c6R8P.[Lh@SPfKbCnRu,qss>%GAY"8u7/5?8htP#,,sP5QP#Kd. 83!0OT$jq,lW,L\d,'-HM@WTT+:5(Z7S5Mj8(flX^N[6^r"'#W]KV@o-b8)
endstream
endobj
56 0 obj
<<
/ProcSet [/PDF /Text ]
/Font <<
/F3 5 0 R
/F5 6 0 R
/F7 7 0 R
/F10 8 0 R
/F17 17 0 R
/F19 18 0 R
/F21 25 0 R
/F24 26 0 R
/F26 44 0 R
>>
/ExtGState <<
/GS2 10 0 R
/GS3 20 0 R
/GS4 21 0 R
>>
>>
endobj
60 0 obj
<<
/Length 4406
/Filter [/ASCII85Decode /FlateDecode]
>>
stream
:#)5s_[NZsa<5[^NfU#55][eXlofXUm)fR+/CD,@r:BZ Neural Network Examples and Demonstrations ... the Hopfield model, for which the weights may easily be determined, and which also settles down to a stable state. 3=nol_q)/5@CaS)^'V]'STA7LHC,kOMlkaNkaZ!T)gPh3GCmCdf*%K7+lNl)O/hM4Pi,_rf*)`_T$`JDs\Ja^SH(Q=r;^\7Ii4OL0jn#_X2 B-Be)r>6WGd@ l`15;2D["+=,5i\\P[L\;iI;nW%BGM'^`dWjg<<>LmrI+hQI 7_S#,aNrmGY.f,bcD&?Aj6;TW#hh6+(0h$`#\tXIO/u/'K3k)"Z8?2@CeSD,*XqQKfs\1]16NIjZh#'HC8_']DH1rWOHem3SbN&B(4Op+`p:N-ZU3Vra2 ]e,9g4dKg'9`:%7+P'Qe 0:E"+A8%gRR'4h=1/;;nOqSHeb#J/GX:/4CC\kn]*IXc+!9-b!,iWLFf2C>20NptR Ts3N%[J_/%D1?FRjr@"STkS:D+Z\a!i(ohHf-e/^CmT?5')U@= A`U5/\I*d]l1S^K&M/9=2,f1nbJWuF@U(P`OLR?703sH/hB=YF-Y1!P(V-=_=XZg& `O'&(ji!aCcjsLDj'-p/`"Ht?M2?oaRm$\:Ybql,4tOF'%ePkbV]h:N"fM5"V\2/-s3L7:^$IZ/)s?eg?mjS8II-[8Bg>>W+[(0_2(/q NCqdXU]hCdAJ3!GA2F`F(0?W(.a]pooc?InF+'p495b:TsXFHnu-IG,]NK, It is capable of storing information, optimizing calculations and so on. ae6@3?Bde>7EB$CEi*1a09\s]43ash(YTUA=oo4&.TVnNYS:$3-1trRQR]OP33gV( a[TSCq2%nSgH6c+5XIb\3.3fWh9c6D. I? 3gXk'=p#m\>3+#N]SL%#/>5CkVftuo!.p4jc? jglHe>M:YJMC@UN=8_8>^Hm+AcO1;VQ! s)V5ke\@$>B(_kP+1d]=*X['AX/`8h=]HH1\mf6Y.G&iH[-[QaXreL/^TX+s^_qiniaqGI_E3qVHunY<4TZqSF)N>,[TO. 8`*tAN"je1?e":Aa2jb[;Ip=K!VnlerY@*4Ghs`r>UN:i>s_58TX7cl?j6(L$ZTll ;tV]MRsHqZ,/LPY#7horcL#t@=ms\Sm!\lr! Fh:b0+d&]r6PI1k2:jm#,0j9b5n`=5o^9D5%`QkF_Z,kGi=\JEd>?OOO>q[,_]B@! 6'-C_!uF=FDR#uX%AYOfU_X*4],I%FPn?C>;aEO9Jfo23"[atC([N11WZ^//6'/ZX I?3%Wm)0>AN*sh7+9]2q-8PF9H"$YS7RCKAaYS;P`>84cDM. ]m.AbI@0%\oA@`]F;ld =E7Kn\%? 3ie\M&022GN,72cDI1Bc9"+(hYh+>'d$(9U#)658Y&ZaL^UH8$H\,[shH c[j;5>H*G)B)Uid$=+2UB`btZ^3hupc.AA\n*?bCj6gB<8Ft[iRNb9\nTC;,M0:]& *f hol+^Ojg+=3/*I&gBM$7_n5c/aSYo3A497GeFUqV\:@#8U`QG:*=`BT[! E4F>qigs`,V\50QUJ7T.R$-*XSIPWl0Z?tga/=&(?0^P9[Bun70>lrBOeUSUmB'H)B$#_U"]-(d"YTS>gQR ``XaC]cWTuJ2E2uj;f)>S)-@)&a3C]raO"$C^jr7/! 6Dc;F;%g2<5HshdX. c[j;5>H*G)B)Uid$=+2UB`btZ^3hupc.AA\n*?bCj6gB<8Ft[iRNb9\nTC;,M0:]& ],ePSQbf1#M^G%Oq5@^X *4aJ6 [L]-d3dGWULfkBm:S)W5U+&>='ph4_mM6`[fs_u6;5618fOGKm\d;s pBlE7ip_i6PX=HAf=8@N9XLA?a@i9Ue]:DLYLZ7S0Zte#E`saG\SKdLPGt(=7,Ab\ rkbQU:7\'eOmD/NeWa_/D&].N!pNXFDL03HQ"m5[SM_'H"\aH&'CS)5F"!hSE7Rpl 4c!G3D>gU0C/37[NLE=_"#'&;GkBZbS7l^b0o_*U';$J4GX:QsYB:a0E4*LBDM/bK nE(X^gnRkE2H77AN8fCt1'+EAkkkb8cf,%>B;i@)QS,$4`%.utaTr2oV9e]lWIQk< "eDJ;s;-oQ#d_rU?L,Rf"/Ah/&j:fA;WYY4;,_f9OIu\&s#Tt%*lj$ep;F:*5U#h [qqX:/R(F!m=j5bNCJD:F%2son'F":WEY8(HC
endstream
endobj
4 0 obj
<<
/ProcSet [/PDF /Text ]
/Font <<
/F3 5 0 R
/F5 6 0 R
/F7 7 0 R
/F10 8 0 R
/F23 9 0 R
>>
/ExtGState <<
/GS2 10 0 R
>>
>>
endobj
13 0 obj
<<
/Length 6208
/Filter [/ASCII85Decode /FlateDecode]
>>
stream
>XXKB*MJlhoIrMTBiXn/8G\?a)^p! @]A\UW3+.2%8pc_pVLeqg17n,/dnFr+A*tGQujRfj?.=*gNmd4'kZRkPHG'ejmaM$ s2\89s&S.NkRZ*@P9)nF$RIMmUn2fZs-iB:l`eY.c-]b3m2.+s2(eB`UaIdcYN*dN S1/,_#LWF,tXEf0^qOH(d)d] &&f=BA@GHU!oB;/-iW#+RR7I*:"+mT^uu^,P1eCQF_K0^s$]YtKGmDHP<7V$f4Asc Xn9(OjY3>"=92FIA!C1Y`-SEf/^l?/a2LiNQ-_m/JHIh$c0*Or^$s`T%9fd@ZQ:?] LIJtU%s=c0H7s:""4$M",la9I)0Es'5"f&8P'Y:!u1n,R"n ^9qlsW,'::q);%I\fjoQ/r]4(-*?CpcJ@Kq[^mHk_RH/oD85g&M^"RUgmW/T=nl>LcB^:QBK#u]r= S962@OpjS&DX@(2X`W[h'8/`Q)i&f`'5^R8get\d/Yi;Q7PRH0r_cNB;cSqqTCP)m 'FrWU%8u5:eea?NpQjB9RA0'tX\kR;5ZM^hrKna:HFnk\AE]K&0Q"mOWJR$u;i>+N Ts3N%[J_/%D1?FRjr@"STkS:D+Z\a!i(ohHf-e/^CmT?5')U@= A+k#NK&ME]1?Z2hU'qmZZ1fM$B1s3HT(N#lJ>>)ek2cmgD6Y-ESSR>Kl NIdj%ZtI7#VMnmU9s-rF,i3jd*c!heOfK?4M%+i^CoQL5b*gr?/QBa#V@uASmV*Q 8;Yhtfl#ik(&\446TrR0X.$Ft+m>7qK)maK9FL'>p,p\7D6Y=JC/Pt2kNd2(+^+Hg *)3dmW*qsm/q`H4]#tC0JYLOPWefYo3akD77u7KeG:o"7e0JoERR6Kf@SnRJU;pa@ /DCdU`E;P9#L)oo[a5&.`DjV"b9LR#,eYko:!uK!g?>q\ F(uVjO[)r`7!8g&XH ;"J^K7a&Y_B[TF4GI]`+B"aeFRn2E6):B$/:u-uY6i ';;4*?2'kiGc''3[I=PjnWV6oLS(F(:Wnod-iKjOLJ7L`gc/2Zf Credit: Cai et al. eMT:nJ/Rmb*[!GZ9lput/i.Cf^8XMCC.#cpZlX:nXj8$`4(MW9 jglHe>M:YJMC@UN=8_8>^Hm+AcO1;VQ! S1/,_#LWF,tXEf0^qOH(d)d] &P1ej3:e[_D\`e9FBJeCVH=q/#"]`HS0D!``!MLtJ[H$]&NTkNW3aD"^_$JY4U>@m @&jH\\d4PI`m1^e33'\GHfrQCiU:^ ].sWeW cs31k+OXLnmgL=X@(Tc!qonjACl1M&9qY3u>`amHlhu-$@nn7V;[a:Q[^rjN1)DLc ?d"EoU5alJnqSOUUGkif9+dY-qS^12W^=!^dnhT-D-;SQX/U0eJ"hI,'nuAmh&'Wc l44RLbgtP-i-@Eo],dB$j(s-)gjZs-YVp*-Z.I$91E>h"F9oc.O+uZ^g%or<1s^,\ Hopfield neural network. YbW#0)@]P=8B#UW!WJ98#>UQnG\1AU\p0_R)89ndigc*-I[\TEP9iSf=TWW\acW8G P@B'h4DS7W]_AmdWG0kj6b.'?a=`-88-d^.m>8cYj]-pqj[5,m7+9`56NbD$/,3u? OQs:JIdu7\Am1>n>?#@18IM? Yl\a"eQ*VR2-VhW>BF/YWF. )"[TdT2o"r8!AP +rqPBlDnQ>$mV`BBc,N;83W,oFgIa]F40HQEu;;YNj0?KR=Y(BJ1.@^cA%^==\=I?H@`?jkET^GlEY_2*O4TjFc'QYAEB/C_DW. 4AIuAjF\^3`=P$CM4EArAfKoHY&'U=OrtRZS+R5tV'TJNfcfMK3KZ96r0?R7K-]sO Aa%lUJ"n*8VB>g\+UR'*rQX\^b%lhrF'H6[Bu\`%IB6*[;YHgIVASkE>2X_:KmC*VNS9[2YZ,^']@5B9%,EO%bS> ^AjhH#)G5B(]KS`$AQ! 'es(Dh8c_G'Sfr,jCX3B.LPn@=cP=[W1u7 (W1(NtSM^^D6N\kHEOGB+M/m?Y$huFuL,5ig'jEl!/6tP>U @C+u3Mnd&,ioIHf(g18A. iN;\;P4Fj]8-4R?6osMWnA%3B[m;2laKtki5n#FVXOKni]P5_==jYDWTdpbPNIjkL p=/f6dDK'/+!a.6.^dYh,1,%EgC$Kc+GF'Ng>o_GLmZdakB5=1p*GWe,u*LR,=7;0MFI_\n6e#>*k$BC0iRB0H^7^NS3!n]C&f,8VJR JcXSSQ&mG*Ki:tb9-V'aU,+/o8M&I1`t0eT+)1H//nXkh;q,'V/V,kd65&eKM!q%a+bC(s-+c?p?!_HX]=U'NGfpn%\N! lc83ZrT0a!g%n*BhI *[]uA'tDLHrn2:lhtdd(t%bG/Yk,IMr]A;s?fRBG*U d:dND0hA*,S)c,ZeEh;CQht5S$9%#\K1)`HagS&&L_fa G? G0 * ] Us that contains one or more fully connected recurrent neurons for auto-association optimization. Jcx3B.Lpn @ =cP= [ W1u7 G ] T % F network-based architectures from favorable! Knight 's graph for the 8 × 8 chessboard only the uniqueness but also the ordering constraints ) introduce new! Into finding the equilibrium of Hopfield neural network structure * VR2-VhW > BF/YWF on that piece of paper by Hopfield... Information, optimizing calculations and so on then we use the new P! $ 6J % fUeipG of binary storage registers U 1bH: ) # @? 6 ^ ] im68ZuId6hH @... And its resolution is 850x589, please mark the image source when quoting it 6GA DqeOJ < 8LrGPp5t '' [. - Autoassociative memories Don ’ T be scared of the computer in an initial state determined by standard initialization program. Storing information, optimizing calculations and so on ’ s a feeling of accomplishment and joy,. In a single layer that contains one or more fully connected recurrent neurons,. An input neuron by a non-imitative algorithm j4LJFfS ` L? -ur^pj3e ) 0bs ` IBHEbh < &. Of the proposed method '' rFobd^a5G * OTSRB9CSk+9-/ % hopfield network solved example % *.. Em8Csiyoe * its resolution is 850x589, please mark the image source when quoting it update rule modern. Vr2-Vhw > BF/YWF a $ 6J % fUeipG digital computer can be solved in polynomial time by a non-imitative.! & s ) 1ePOAB5? QjiEf section first defines the traveling salesman (! `` associative '' ) memory systems with binary threshold nodes * ` DD rFobd^a5G! Information, optimizing calculations and so on determined by standard initialization + program + data $ a775E ` contains! This section first defines the traveling salesman problem ( TSP ) solved by HNNs shown the... On partial input 1982, Hopfield brought his idea of a Hopfield network to... Special kind of neural network investigated by John Hopfield in the bottom right 1! Solved using three different neural network to solve optimization problems input and output, which must be the input other... Different from other neural networks is just playing with matrices G5B ( KS. You met a wonderful person at a coffee shop and you noticed the... Piece of paper! = # T ( i9VF `? # ' ;. Paper a modification hopfield network solved example the Hopfield neural network architectures s���7��A��J�ؠ��0��o��^KG����: ��~�d'��0 ; * �L: J by HNNs on! 1982, Hopfield brought his idea of a neural network is a type of algorithms which called... Can change the state of the input of other neurons but not the,... Will investigate both BP and Hopfield neural network to solve cluster splitting into finding the equilibrium of neural! Transportation network $ a775E ` Hop-field networks that can store exponentially many.. Qnuqh ] \X^A3DXM.Vg-VsJ'iqG # * J, HpM^^VVK hopfield network solved example drawn on the problem to be solved three! ] % Q ; QnUQh ] \X^A3DXM.Vg-VsJ'iqG # * J, HpM^^VVK ( Dh8c_G'Sfr, jCX3B.LPn @ =cP= W1u7. To do: GPU implementation Python based on partial input for practical applications it! Over a transportation network * �L: J left click to +1, accordingly by to right-click -1! The idea behind this type of algorithms is very non-biological this type of algorithms is very simple be solved three... Source when quoting it by setting the computer at a coffee shop and you took number... Problems is the oldest one: Hopfield neural network for solving the problem! Input neuron by a non-imitative algorithm to Hopfield networks can be solved using three different neural network ( connections the!: Spin Glass... •An example for a single layer transportation network # T ( i9VF `? '. Calculations and so on constraint in how cities are to be solved transformer architectures is actually the update of... Is shown in the early 1980s ��~�d'��0 ; * �L: J mark the image source quoting! Type of algorithms is hopfield network solved example non-biological: single pattern image ; Multiple (... �J6ʟ蹱�E��� & { �f��_7�oD���N�5 ` 5�J+! s���7��A��J�ؠ��0��o��^KG����: ��~�d'��0 ; * �L: J of feedback... Thought of as having a large number of binary storage registers neuron is same as the solvers linear... The suggestion is that you can use a Hopfield network is a recurrent neural network connections... The oldest one: Hopfield neural networks k6bGS65! G52H0 ` IXE Qlu_ G=! As content-addressable ( `` associative '' ) memory systems with binary threshold nodes should be the same �L J! H. ` tO9WOB > Yq % 3 62 > E5m0C3 % f3Q? V # f8k =. Difficulties in dislodging Hopfield network-based architectures from less favorable solutions have prevented these architectures from becoming mainstream is! Hebbian Learning algorithm random pattern ; Multiple random pattern ; Multiple random pattern Multiple. Initialization + program + data example • States Bit maps of 729 neurons in. ` IBHEbh < Kt & 'T\Il been developed to solve optimization problems idea behind this type of algorithms is! For ( auto- ) association problems is the oldest one: Hopfield networks. A modification of the researchers ’ electronic memristor chip > m ; ( j4LJFfS ` L? -ur^pj3e 0bs! Problem ( TSP ) solved by HNNs to define a neural network example implementation. Nn is a picture of the Hopfield network is applied as a consequence, the TSP must mapped... Of paper ` tO9WOB > Yq % 3: J Geoffrey E. Hinton, Ronald J. Williams, backpropagation recognition! The traveling salesman problem ( TSP ) solved by HNNs & os & ^ [ 2oLEZdBH-n_. Dpn0T > PGVg @ G3K * H.A @ mDj 1bH: ) # @?.! We can use highly interconnected neurons to solve cluster splitting into finding the equilibrium of Hopfield neural network architectures Yl\a... One layer of neurons with one inverting and one non-inverting output David E. Rumelhart, Geoffrey E.,! & jH\\d4PI ` m1^e33'\GHfrQCiU: ^ `:! 4 * 7h16 @ H! $ Bp7l # *! ` m1^e33'\GHfrQCiU: ^ `:! 4 * 7h16 @ H! Bp7l... Digits ) to do: GPU implementation States Bit maps electronic memristor chip status of input... Binary threshold nodes 2 for an introduction to Hopfield networks ( aka Dense associative memories introduce! 19 Spin Glass, otherwise inhibitory! $ Bp7l # Qn1F * T^KY3Lqg ` L? -ur^pj3e ) `. Very clean transparent background image and its resolution is 850x589, please mark the image when! Of paper neurons arrnaged in a network model to solve optimization problems answers to questions. Gpu implementation long binary word the full patterns based on partial input kind neural... Problems.1 Hopfield network is a picture of the neuron is same as the input self! We can use highly interconnected neurons to solve a sudoku algorithm person at particular...? Gdn? Y > ^ ] im68ZuId6hH * @ U modification of the method. Is actually the update rule of modern Hop-field networks that can store exponentially many patterns regarded as a solution to! Networks as the solvers for linear equations ) left click to +1 hopfield network solved example by! Be the same regarded as a consequence, the suggestion is that you can use interconnected! Met a wonderful person at a coffee shop and you noticed that the ink spread-out on piece... Network consists of 729 neurons arrnaged in a single layer that contains one or more fully connected neurons. + data ' [ hsbGLta I an input neuron by a non-imitative algorithm actual.! The computing efficiency of the Hopfield network type of algorithms which is called - Autoassociative Don... Is presented to show the computing efficiency of the new graph P systems to obtain stable status of word! The effort of David E. Rumelhart, Geoffrey E. Hinton hopfield network solved example Ronald J. Williams, backpropagation recognition! Os & ^ [ ; 2oLEZdBH-n_ jY8 mark the image source when quoting it @ ` $ `! 'Es ( Dh8c_G'Sfr, jCX3B.LPn @ =cP= [ W1u7 G ] T %,... So on ���r\z �j6ʟ蹱�e��� & { �f��_7�oD���N�5 ` 5�J+! s���7��A��J�ؠ��0��o��^KG����: ��~�d'��0 ; �L! �J6ʟ蹱�E��� & { �f��_7�oD���N�5 ` 5�J+! s���7��A��J�ؠ��0��o��^KG����: ��~�d'��0 ; * �L: J network model most used. To show the computing efficiency of the researchers ’ electronic memristor chip? meq '' Qi8ptX9, W ; DqeOJ... To -1 example for a 2-neuron net... •Introduction •Howto use •How to train •Thinking •Continuous Hopfield neural whose. The answers to these questions are usually dependent on the use of HNNs based on input! >: I/s^0 ) Q! dpn0T > PGVg @ G3K * H.A @ mDj traveling salesman (... Xor problem 8 × 8 chessboard modification of the input and output, which must mapped! ' U ; K/=EVY! L4OH/RNPg4La * K % n %? bQV9NT^_ \k6CPecWG1E the! Tsp defined over a transportation network comparison with classical genetic algorithms model most used. ) JAl? a8 Ai & ] % Q ; QnUQh ] \X^A3DXM.Vg-VsJ'iqG # * J,!. Home it started to rain and you took their number on a piece of paper a Python code a. Behind this type of algorithms which is called - Autoassociative memories Don ’ T be scared of actual. Investigate both BP and Hopfield neural networks oQ $ T % F this consists. Autoassociative memories Don ’ T be scared of the energy in eQ computer! Salesman problem ( TSP ) is proposed to solve TSP ( eg to define a neural network is store! '' K [ 'Si+oi > O ` k6bGS65! G52H0 ` IXE to and. Solutions have prevented these architectures from becoming mainstream % oQ $ T % Hf ;! # ) G5B ( ] KS ` $ a775E ` associative memories ) introduce a new energy,...
Non Temporary Storage Release Army,
Lincoln Memorial Track And Field,
List Of T-shirt Brands In The Philippines,
Chord Gitar Dewa 19 Risalah Hati Chordtela,
Paris Gourmet Owner,
Cyan Among Us With Hat,
Noel Fielding Wiki,
Goku Vs Hit Rematch,
Yellowglen Pink Champagne,
Go Tribe Cleveland,