1

M U

1. Tnh cp thit ca ti

Trong rt nhiu lnh vc nh iu khin, t ng ha, cng ngh

thng tin, nhn dng c i tng l vn mu cht quyt

nh s thnh cng ca bi ton.

Mt nhc im khi dng mng nron l cha c phng php lun

chung khi thit k cu trc mng cho cc bi ton nhn dng v iu

khin m phi cn ti kin thc ca chuyn gia. Mt khc khi xp x

mng nron vi mt h phi tuyn s kh khn khi luyn mng v c

th khng tm c im ti u ton cc... Hin nay, vic nghin cu

cc thut ton tm nghim ti u ton cc khi luyn mng nron

c mt s tc gi nghin cu p dng. Tuy nhin khi s dng

mng nron xp x mt s i tng phi tuyn m mt li sinh ra

c dng lng khe, vic hun luyn mng gp rt nhiu kh khn.

Ni dung ti s i nghin cu mt thut ton tm im ti u ton

cc trong qu trnh luyn mng nron bng thut ton vt khe c s

kt hp vi gii thut di truyn.

2. Mc tiu ca lun n

- xut m hnh kt hp thut ton vt khe v gii thut di truyn

hun luyn mng nron.

- Xy dng b cng c phn mm luyn mng nron cho mt s bi

ton c mt li c bit, lm c s b sung vo Neural Toolbox

Matlab.

3. Ni dung chnh ca lun n

- Nghin cu l thuyt v thut ton vt khe v xy dng thut ton

tnh bc hc vt khe.

- Xy dng thut ton hun luyn mng nron bng k thut lan

tuyn ngc kt hp vi thut ton vt khe.

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- xut thut ton hun luyn mng nron bng k thut lan truyn

ngc c s dng gii thut di truyn kt hp vi thut ton vt

khe.

- Vit v ci t chng trnh hun luyn mng nron trn C++.

- Vit v ci t chng trnh hun luyn mng nron trn Matlab.

CHNG 1

MNG NRON V QU TRNH HC CA MNG NRON

1.1. Gii thiu v mng nron v qu trnh hc ca mng

nron

1.1.1. Mng nron v cc phng php hc

Mng nron nhn to, gi tt l mng nron, l mt m hnh x l

thng tin phng theo cch thc x l thng tin ca cc h nron sinh

hc. N c to ln t mt s lng ln cc phn t (gi l nron)

kt ni vi nhau thng qua cc lin kt (gi l trng s lin kt) lm

vic nh mt th thng nht gii quyt mt vn c th no .

Mt mng nron nhn to c cu hnh cho mt ng dng c th

(nhn dng mu, phn loi d liu,...) thng qua mt qu trnh hc t

tp cc mu hun luyn. V bn cht hc chnh l qu trnh hiu

chnh trng s lin kt gia cc nron sao cho gi tr hm li l nh

nht.

C ba phng php hc ph bin l hc c gim st, hc khng gim

st v hc tng cng. Hc c gim st l phng php c s

dng ph bin nht, trong tiu biu l k thut lan truyn ngc.

1.1.2. nh gi cc nhn t ca qu trnh hc

1.1.2.1. Khi to cc trng s

Do bn cht ca gii thut hc lan truyn ngc sai s l phng

php gim lch gradient nn vic khi to cc gi tr ban u ca

cc trng s cc gi tr nh ngu nhin s lm cho mng hi t v cc

gi tr cc tiu khc nhau.

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1.1.2.2. Bc hc

Vic chn hng s hc ban u l rt quan trng. Vi mi bi ton ta

li c phng n chn h s hc khc nhau. Khi mt qu trnh hun

luyn theo k thut lan truyn ngc hi t, ta cha th khng nh

c n hi t n phng n ti u. Ta cn phi th vi mt s

iu kin ban u m bo thu c phng n ti u.

1.2. Nhn dng h thng s dng mng nron

1.2.1. Nhn dng h thng

1.2.1.1. Ti sao phi nhn dng

Bi ton nhn dng l mt vn t ln hng u trong nhiu cc

lnh vc khc nhau nh: in t y sinh, in t vin thng, h thng

in, t ng ha v iu khin V d nh: nhn dng vn tay,

nhn dng k t, nh, ting ni, pht hin v chn on bnh...

1.2.2. Nhn dng h thng s dng mng nron

1.2.2.1. Kh nng s dng mng nron trong nhn dng

Xt trng hp i tng phi tuyn c phc tp cao, nu s dng

phng php gii tch thng thng nhn dng s rt kh khn,

thm ch khng thc hin c do s hiu bit ngho nn v i

tng. V vy cc nh khoa hc a ra tng l s dng cng c

tnh ton mm nh h m, mng nron, i s gia t xp x -

chnh l nhn dng i tng. Mng nron l mt trong nhng cng

c hu hiu nhn dng m hnh i tng, bng phng php ny

ta khng bit c m hnh ton thc s ca i tng nhng hon

ton c th s dng kt qu xp x thay th i tng.

1.2.2.2. M hnh nhn dng h thng s dng mng nron

Nhn dng gm: nhn dng m hnh v nhn dng tham s.

Nhn dng m hnh l qu trnh xc nh m hnh ca i tng v

thng s trn c s u vo v u ra ca i tng. M hnh thu

c sau khi nhn dng gi l tt nu n th hin c ng i

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tng. Nh vy c th s dng m hnh thay cho i tng d

bo, kim tra v iu khin.

Mng nron c hun luyn

m hnh ha quan h vo ra

ca i tng. Nh vy quy

trnh nhn dng m hnh c

bn cht l thut ton luyn

mng. Cu trc mng nron

gii bi ton nhn dng m hnh rt a dng, ty thuc vo tng bi

ton c th.

Nhn dng tham s chnh l hun luyn mng, c biu din trn

Hnh 1.2. Tn hiu sai s e y y l c s cho qu trnh luyn mng.

Mng nron y c th l mng nhiu lp hoc cc dng khc v

c th s dng nhiu thut luyn mng khc nhau.

1.2.2.3. Nhn dng h thng s dng mng nron

Nhn dng h thng cn hai giai on l la chn m hnh v ti u

tham s. i vi mng nron la chn s nt n, s lp n (cu trc

ca mng) tng ng vi m hnh la chn. Mng c th c

hun luyn theo kiu gim st vi k thut lan truyn ngc, da vo

lut hc sai s hiu chnh. Tn hiu sai

s c lan truyn ngc qua mng.

K thut lan truyn ngc s dng

phng php gim gradient xc

nh cc trng ca mng v vy tng

ng vi ti u tham s.

1.3. Mt li c bit khi luyn

mng nron

1.3.1. Mt li c bit khi luyn

mng nron Hnh 1.3: Mt sai s dng lng khe

i tng

Mng nron

u y

y

e -

Hnh 1.2: M hnh nhn dng c bn

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Hnh 1.3 m t mt mt sai s, c mt vi iu c bit cn ch i

vi mt sai s ny: dc bin i mt cch mnh m trn khng

gian tham s. V l do , n s kh m la chn mt tc hc

ph hp cho thut ton gim dc nht.

1.3.2. V d v bi ton dn n mt li c bit

c im khe ca cc bi ton ti -u ho trong ngnh nhit[28]

S dng mng nron nhn dng i tng

Vi cc h thng c phi tuyn cao th lm th no nhn dng

i tng lun l mt cu hi t ra vi chng ta. V tnh phi tuyn

ca cc mng nron (hm kch hot phi tuyn), chng c dng

m t cc h thng phi tuyn phc tp.

Luyn mng nron c hai qu trnh, qu trnh nh x v qu trnh

hc. Hc thc cht l qu trnh lan truyn ngc. Thc hin k thut

lan truyn ngc chnh l gii bi ton ti u tnh vi hm mc tiu

l mt sai s.

Hnh dng ca mt sai s ph thuc vo s lp nron v loi hm

kch hot. Trong khi mt sai s vi mng tuyn tnh mt lp c mt

cc tiu n v dc khng i, mt sai s vi mng nhiu lp c

th c nhiu im cc tiu cc b, c th b ko di, un cong to

thnh khe, trc khe v dc c th thay i mt di rng trong

cc vng khc nhau ca khng gian tham s.

Thc t, vic chn hm kch hot nh th no, chn s lp mng

nron bng bao nhiu ph thuc vo i tng cn xp x. Nh vy,

do phc tp ca i tng cn xp x khc nhau nn hm mc tiu

rt khc nhau v dn n qu trnh hc (gii bi ton ti u) c th

rt phc tp. c bit khi i tng cn xp x dn n hm mc tiu

c dng lng khe (v d nh i tng nhit) th qu trnh hc rt

kh khn thm ch khng hi t nu ta s dng cc b cng c c

trong Toolbox ca Matlab.

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1.4. M phng qu trnh luyn mng nron khi s dng

Toolbox ca Matlab

1.4.1. M phng hun luyn mng nron c mt li bnh

thng

Xt h thng phi tuyn cn nhn

dng c m hnh ton hc sau:

f (u) = 0.6 sin( .u) + 0.3 sin(3. .u) + 0.1

sin (5. .u)

Tn hiu vo: u (k) = sin(2 .k/250)

Mng nron s dng l mng truyn

thng 3 lp c mt u vo v mt

u ra.

1.4.2. M phng hun luyn mng nron c mt li c bit

minh ha, tc gi xut cu trc mng n ron nhn dng cc

ch s: 0, 1, 2,...,9. Trong hm sigmoid c s dng lm hm

kch hot. 1/ (1 exp(-x))f

Hnh 1.6 trnh by kt qu ca qu trnh luyn mng cho bi ton

nhn dng ch vi cc k thut lan truyn ngc sai s theo phng

php Batch Gradient Descent (traingd), Batch Gradient Descent with

Momentum (traingdm), Variable Learning Rate (traingda, traingdx).

Cc phng php ny u c tch hp trn Neural Network

Hnh 1.5: Cu trc mng nron cho nhn dng ch

Hnh 1.4: K nguyn luyn mng v d 1

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Toolbox ca Matlab. Nhn chung cc phng php u cho kt qu

kh tt, tuy nhin t c chnh xc nh mong mun th thi

gian cn thit cho luyn mng l kh ln. Thm ch c trng hp tn

hiu li hu nh thay i rt t qua cc chu k luyn mng.

1.5. Tng quan v tnh hnh nghin cu trong v ngoi nc

1.6. Kt lun chng 1

Trong chng 1, tc gi phn tch cc nhn t trong qu trnh hc

ca mng nron. Tc gi nhn thy rng, kt qu luyn mng nron

ph thuc rt ln vo gi tr ban u ca vec-t trng s v bc

hc. Vic mng s hi t n im ti u ton cc hay khng nhiu

khi cn ph thuc vo s may mn do vic chn gi tr khi to l

ngu nhin. Thm na, vic la chn bc hc s bng bao nhiu

c th hi t hay t nht l tng tc hi t l mt cu hi cng

c t ra, c bit khi mt li c dng c bit. minh chng

cho iu tc gi a ra 2 v d: v d 1, khi mt li dng

bnh thng, s dng b cng c trong Toolbox ca Matlab luyn

mng, mng luyn thnh cng sau 65 bc tnh. n v d th 2

v nhn dng ch vit tay th thi gian luyn mng lu hn rt nhiu,

thm ch tn hiu li cn thay i rt t qua cc chu k luyn mng.

Hnh 1.6: Cc kt qu luyn mng n ron vi cc phng php

lan truyn ngc khc nhau (traingd, traingdm, traindx, trainda)

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gii quyt vn ny, cn thit phi tm ra mt thut ton hiu

chnh cc bc hc nhm rt ngn thi gian hi t ca mng ng

thi cng trnh c vn cc tr a phng.

CHNG 2: THUT TON VT KHE TRONG

QU TRNH LUYN MNG NRON

2.1. Thut ton vt khe

Cho bi ton ti u v gii bi ton ti u khng iu kin:

MinJ(u) u En (2.1)

u l vec-t trong khng gian

Euclide n chiu

Cng thc lp bc th k:

uk+1

= uk+ k s

k, k = 0,1,(2.2)

trong : u : vect bin ca hm

mc tiu J(u) ti bc lp th k;

k l di bc ca hm theo hng chuyn ng sk.