Historie a rozd lení neuronových sítí (NS) 1943

Úvod
+LVWRULHDUR]GOHQtneuronových sítí (NS)
Následuje historické mapování vývoje NS v kontextu KDO a KDY zavedl CO (myšleno
EXGH QHXURQRYp VtW 3RþiWHN ]DþtQi pracemi neurofyziologa Warren McCullocha a
matematika Waltera Pittse z roku 1943. 1iVOHGXMtFtSHKOHGVWUXþQFKDUDNWHUL]XMWHStVOXãQp
metody NS.
1943 - Warren McCulloch a Walter Pittse
1949 - Donald Hebb
1958 - Frank Rosenblatt, perceptron
1959 – ADALINE
MP-perceptron
50. - 60. léta
1967 - 1982 Období stagnace
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1987 - Vzestup popularity NS
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1943 - Warren McCulloch a Walter Pittse
=iNODG\ QHXURQRYêFK VtWt SRORåLOL :DUUHQ 0F&XOORFK D :DOWHU 3LWWV YþOiQNX Ä$ /RJLFDO
&DOFXOXV RI WKH ,GHDV ,PPDQHQW LQ 1HUYRXV $FWLYLW\³ XYHHMQQê Y roce 1943 v Bulletin of
Mathematical Biophysics. VWRPWRþOiQNXY\WYRLOLPDWHPDWLFNêSRSLVQHXURQ$DXNi]DOLåH
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MHåPDMtMHKRYêVWXSMDNRYVWXSMHMHKRKRGQRWDVWHMQiDQMDNRXIXQNFLMHMtPLåDUJXPHQW\
MVRXYVWXS\DIXQNþQtKRGQRWDMHYêVWXSHPGDQpKRQHXURQX
Obr. 1 Model neuronu jak ho navrhli Warren McCulloch a Walter Pittse
1
1949 - Donald Hebb
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V roce 1949 byla vydána kniha The Organization of Behavior od Donalda Hebba. Poskytla
QiYRG NWHUDN SRXåtYDW XþtFt pravidlo pro synapse QHXURQ$ LQWHUIDFH ,QVSLURYDO VH
P\ãOHQNRXSRGPtQQêFKUHIOH[$NWHUpMVRXSR]RURYDWHOQpXåLYRþLFK$2YOLYQLODGXGDOãtFK
YGF$DþNROLYOpWDQHSLQHVOD]iVDGQtSRNURNYREODVWLQHXURYêSRþW$3UYQtYODãWRYND
vWpWR REODVWL E\O QHXURSRþtWDþ Snark. Byl postaven v roce 1951 a u jeho zrodu stál Marvin
0LQVN\%\OYHOLFH~VSãQêP] technického hlediska, automatický adaptoval váhy, ale nikdy
VHQHVWDOXåLWHþQêP-HGQRGXãHY]QLNODE\H[LVWRYDO
1958 - Frank Rosenblatt, perceptron
Frank Rosenblatt zobecnil model neuronu v roce 1957 na tzv. perceptron NWHUê SRþtWDO
s reálnýmL þtVO\ -HGQi VH R SHYQRX DUFKLWHNWXUX MHGQRYUVWYp VtW V “n” vstupními a “m”
YêVWXSQtPL QHXURQ\ %\O LQVSLURYiQ OLGVNêP RNHP 9\ãHO ]H ]MLãWQt I\]LRORJ$ åH VtWQLFH
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3HUFHSWURQRYi Vt" MH SRGOH I\]LRORJLFNpKR Y]RUX WDNp WtYUVWYi 9VWXSQt YUVWYD IXQJXMH
MDNR Y\URYQiYDFt -HMtP ~NROHP MH PDSRYiQt GYRXUR]PUQpKR SROH þLGHO QD MHGQRUR]PUQê
YHNWRU SURFHVRURYêFK HOHPHQW$ 7XWR GUXKRX YUVWYX WYRt GHWHNWRU\ U\V$ St]QDN$ .DåGê
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neuron.
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SUYQt QHXURSRþtWDþ -PHQRYDO VH Mark I Perceptron D E\O QDYUåHQ SUR UR]SR]QiYiQt
]QDN$=QDNVHSURPtWDOQDVYWHOQRXWDEXOL7DE\ODPRQLWRURYiQDPDWLFt[IRWRVQtPDþ$
,QWHQ]LWDFHONRYpKRSRþWXVQtPDþ$E\ODYVWXSHPGRQHXURQRYpVtWSHUFHSWURQ$3RþtWDþ
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1959 - ADALINE
Adaline se objevuje jako další typ neuronového prvku, který byl velmi podobný
SHUFHSWURQX $NWLYQt G\QDPLND VH X WRKRWR PRGHOX OLãLOD WtP åH YêVWXS\ VtW E\O\ REHFQ
2
reálné a jednotlivé ADALINE realizovali lineární funkci. Bernard Widrow a jeho studenti byli
DXWRU\$'$SWLYQtKR/,1HiUQtKR(OHPHQWX6iP:LGURZVH]DVORXåLORY]QLNSUYQtNRPHUþQt
organizace vSRORYLQ OHW NWHUi VH ]DREtUDOD VWDYERX QHXURSRþtWDþ$ D MHMLFK VRXþiVWHN
6SROHþQRVW VH MPHQRYDOD Memistor Corporation =iURYH DE\ SRGSRLO VSUiYQRVW MHKR
QiYUKX UHDOL]RYDO VH VWXGHQW\ DGX MHGQRGXFKêFK ~ORK .RPHUþQ VH Wpå UHDOL]RYDO 5RJHU
%DUURQ D /HZH\ *LOVWUDS NWHt YURFH ]DORåLOL SUYQt ILUPX ]DPHQRX QD DSOLNDFL
QHXURYêSRþW$9êVOHGN\O]HQDOp]WY knize Nilse Nilssona Learning Machines (1965).
2EU$UFKLWHNWXUDSHUFHSWURQRYpVtW
MP-perceptron
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PD[LPiOQ]MHGQRGXãLOL5RVHQEODWW$YSHUFHSWURQWDNåHYêVOHGNHPMHMHGQRYUVWYiQHXURQRYi
Vt" -HMt GLGDNWLFNRX SHGQRVWt MH åH VH YQt Gi SRPUQ VQDGQR JHRPHWULFN\ LQWHUSUHWRYDW
XþtFtSURFHV
50. - 60. léta
3HORP OHW ]D]QDPHQDO ~VSFK .DUO 6WHLQEXFK NWHUê Y\YLQXO model binární
DVRFLDWLYQt VtW 1D UR]GtO RG SDPWL NODVLFNêFK SRþtWDþ$ NG\ NOtþ NY\KOHGiQt SRORåN\
vSDPWL MH DGUHVD X DVRFLDWLYQt SDPWL GRFKi]t NY\EDYHQt XUþLWp XGiORVWL þL LQIRUPDFH QD
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autoasociativní a heteroasociativní 8 SUYQtKR GUXKX ãOR XSHVQQt YVWXSQt LQIRUPDFH D X
heteroasociativní dochází kY\EDYHQtXUþLWpVGUXåHQpLQIRUPDFHQD]iNODGYVWXSQtDVRFLDFH
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3
1967 - 1982 Období stagnace
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]REHFQQêFKPRGHO$'RVSOLN]iYUXåHQHXURQRYpVtWQHPRKRXQDKUDGLWNODVLFNpPHWRG\
SURWRåH V jejich pomocí nelze simulovat všechny logické zákony ( pomocí jednovrstvého
SHUFHSWURQX QHO]H HãLW ;25 SUREOpP 9\VYWOLOL åH QXWQi RPH]HQt PRKRX EêW VLFH
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-HMLFKNULWLNDE\ODVLFHRSUiYQQiDOHSHVWRXQiKOHQi
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]DStþLQLOL ~WOXP YH Yê]NXPX XPOêFK QHXURQRYêFK VtWt 8Ni]DO\ VH WHRUHWLFNp PH]H
PRåQRVWtMHGQRGXFKêFK16DYê]NXPVHQDGORXKiOpWDRGNORQLOVPUHPNXPOpLQWHOLJHQFL
Ale ani vWpWRREODVWLVHQHGDLORYãHFR VH RþHNiYDOR 9ê]NXP ]HMPpQD ] technologických
G$YRG$SRVWXSRYDOYHOPLSRPDOX9 roce 1983 došlo v USA k novým obrovským investicím
do výzkumu neuronových sítí. Byla to DARPA (Defence Advance Research Project
Association). VWRPWR REGREt E\O YHãNHUê Yê]NXP ILQDQFRYiQ SHGHYãtP ]H VRXNURPêFK
]GURM$
Obr. 3 Neuron
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jsou zQtRGYR]HQDSUDYLGODSURXþHQtDY\EDYRYiQt
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nalezený vzor.
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.RKRKHQRYXVt"SDWtPH]LVDPRUJDQL]XMtFtVHVHVtW=iNODGQtP\ãOHQND.RKRKHQRY\VtW
vychází zSR]QDWNX åH PR]HN SRXåtYi SUR XFKRYiQt LQIRUPDFH YQLWQt SURVWRURYRX
UHSUH]HQWDFL GDW 3LMDWi GDWD ]RNROt MVRX QHMSUYH WUDQVIRUPRYiQD GR YHNWRU$ NWHUp VH
]DNyGXMt GR QHXURQRYp VtW 9WãLQD QHXURQ$ YPR]NRYp N$åH MH RUJDQL]RYiQD
vGYRXGLPHQ]LRQiOQtPSURVWRUXWMURYLQ6SRMHPH]LQHXURQ\YHGRXSRX]HPH]LVRXVHGQtPL
QHXURQ\ .RKRKHQ$Y ]iNODGQt PRGHO Y\FKi]t ]WRKRWR SR]QDWNX D SURWR MH YWãLQRX WDNp
GYRXGLPHQ]LRQiOQt DOH DOJRULWPXV SLSRXãWt L MLQp XVSRiGiQt YêVWXSQtFK QHXURQ$ 3RþHW
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Struktura neuronu v.RKRKHQRYVtWLMHRGOLãQiRGQHXURQXYSHUFHSWURQRYVNpVtWL3RþHW
YVWXS$NWHUpSLFKi]HMtGRQHXURQXMHURYHQSRþWXYVWXS$GR.RKRKHQRY\VtW9iK\WFKWR
YVWXS$ VORXåt N]DNyGRYiQt Y]RU$ NWHUp UHSUH]HQWXMt SHGORåHQp Y]RU\ VWHMQ MDNR X
SHUFHSWURQX9ODVWQtSHQRVRYRXIXQNFLW\WRQHXURQ\QHPDMtMHGLQRXRSHUDFtNWHURXQHXURQ
SURYiGt MH YêSRþHW Y]GiOHQRVWL RGFK\ON\ SHGORåHQpKR Y]RUX RG Y]RUX ]DNyGRYDQpKR YH
vahách daného neuronu.
9êVWXSQt QHXURQ\ MVRX PH]L VHERX Y]iMHPQ SURSRMHQ\ DOH MHQ VH VRXVHGQtPL QHXURQ\
.DåGê YVWXS MH SURSRMHQ VNDåGêP QHXURQHP PtåN\ 9êVWXS X .RKRKHQRY\ VtW GH IDFWR
QHH[LVWXMH .DåGê QHXURQ YPtåFH MH StPR YêVWXSHP 3RþHW YêVWXS$ MH WHG\ URYHQ SRþWX
QHXURQ$ .RQNUpWQt SRþHW QHXURQ$ ]iYLVt QD GDQp DSOLNDFL D MH YSRGVWDW OLERYROQê ýtP MH
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URVWHYêSRþHWQtþDV
1987 - Vzestup popularity NS
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INNS (International Neural Network Society).9]QLNiDGDVYWR]QiPêFKþDVRSLV$MDNRMVRX
Neural Networks, Neural Computation, IEEE Transactions on Neural Networks.
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DGDXQLYHU]LWQDFHOpPVYW]DNOiGiQRYpYê]NXPQp~VWDY\VWtPWR]DPHQtP
$57Vt"7KH$GDSWLYH5HVRQDQFH1HWZRUNV
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SRãNR]HQt MLå GtYH XORåHQp LQIRUPDFH 7HQWR HIHNW P$åHPH QHMOpSH YLGW QD YtFHYUVWYp
SHUFHSWURQRYp VtWL 3L WUpQRYiQt VtW QD QRYpP Y]RUX P$åH GRMtW NH ]KURXFHQt FHOp VtW WM
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5
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(neuroprocesorech).
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6
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neuronových sítí od ostatních metod.
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ãHVWQiFWVRXWåtFtFKN = 16) ?
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NWHUêY\FKi]t]HVNXWHþQpKR DOJRULWPX Y\D]RYiQt WM YSUYQtP NROH VH KUiþ$ UR]GOt
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UR]GOtGRGYRMLF'RWHWtKRNRODSRVWXSXMtMHQKUiþLNWHtVHUR]GOtGRGYRMLF9H
þWYUWpP ILQiOQtP NROH VRXWåt MLå MHQ GYD SRVOHGQt KUiþL 6RXWå NDåGp GYRMLFH MH
]DSRþWHQDMDNRMHGHQ]iSDVFRåO]HY\MiGLWQiVOHGXMtFtPY]WDKHP
P = 16/2 + 8/2 + 4/2 + 2/2 = 8 + 4 + 2 + 1 = 152GHKUiWVHPXVtWHG\]iSDV$
=FHOD UR]GtOQê StVWXS MH SRXåLW ORJLFNpP HãHQt SUREOpPX -HVWOLåH SL NDåGpP ]iSDVX
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P = N – 1 = 16 – 1 = 15
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N:
p:
8
7
12
11
24
23
4
3
atd.
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N:
p:
16
15
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problém, se kterým se nesetkala vSURFHVXXþHQt
Typy úloh pro neuronové sít:
•
•
•
•
•
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3UHGLNFHþDVRYêFKDGNUiWNRGREpSHGSRYGL
Modely (regulace)
Komprese dat
2SWLPDOL]DFHQDSREFKRGQtFHVWXMtFt
1HXURQRYpVtWVHSRXåtYDMtSHGHYãtPMDNRXQLYHUViOQtDSUR[LPiWRU
7