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1:一般模式的BP: a! C) B8 q# q1 r3 x* U: i
clc. r# k' X( Z5 ~; C) N2 z2 I$ H
P=[-1 -1 2 2 ;0 5 0 5];4 f" _- Q: Q8 l/ f, a; o* m$ W5 ?
T=[-1 -1 1 1];
7 j8 h( N- F- K/ pnet=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traingd');
' h6 V$ [. S, t( [net.trainParam.show=50;
+ @8 b" n) B8 D( j6 b! w3 ~net.trainParam.lr=0.05;
* A# u' w4 x. z, L- c: q0 qnet.trainParam.epochs=300;
S- F' J+ U# z7 _' F8 e2 A7 {net.trainParam.goal=1e-5
) p' v9 u: S( E9 {5 n5 ^4 d[net tr]=train(net,P,T);8 R8 b1 }: J g' i) j8 V
9 H4 W! e7 m* W' t7 c: w2：加入动量的BP" \- H2 G+ r R
clc
/ |) r2 Z1 `; E: i4 CP=[-1 -1 2 2 ;0 5 0 5];
! A; f. S5 [$ J0 }" ~+ ?T=[-1 -1 1 1];; o9 f Y5 D% v# q: U
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traingdm');
5 Z6 ]! ]. U' }$ e2 N1 {. s$ f2 onet.trainParam.show=10000;
" j/ C* k5 L; s3 e" w/ d, Rnet.trainParam.lr=0.05;* z, B1 ]% L( o4 _0 Z" R) ~% ]
net.trainParam.mc=0.9;
, }4 i# r |" I$ Inet.trainParam.epochs=10000;0 ~- G+ D' }( x k
net.trainParam.goal=1e-5*100
+ K2 H. m- e# _" e( J1 K[net tr]=train(net,P,T);: V8 q% s2 R6 d) d; {% l
# E3 O1 C; U' v% K$ ^3：自适应LR变步长：4 t. Y3 w: |, q* s
clc2 N$ N2 ?% e& _' K$ V
P=[-1 -1 2 2 ;0 5 0 5];
& n3 _% B5 [4 [6 O+ RT=[-1 -1 1 1];
2 k" X; R) e0 n; Lnet=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traingda');
6 B6 V; _. [1 Z) u" Vnet.trainParam.show=10000;! l3 Y* v5 ^) T9 k" C. a2 `
net.trainParam.lr=0.05;1 w) n1 ]6 W# y |0 q5 {. V
net.trainParam.lr_inc=1.05;$ v7 c5 J# N1 B. v) O( H% Z( e3 I5 P
net.trainParam.epochs=10000;
3 Q6 D. Z# \& @6 J0 k& Mnet.trainParam.goal=1e-5*100
c b0 d4 f e" N[net tr]=train(net,P,T);
9 O* E5 N% e: Q* T. n+ W+ o- P5 ~4 U D/ P8 p+ P* r0 c
0 c: X0 `& @: a6 U+ ^
4：弹性梯度法
! X7 ^3 S- x8 @4 l( K% G6 N" V3 C4 q: Mclc/ |# c4 R% c f$ K
P=[-1 -1 2 2 ;0 5 0 5];
6 a6 X0 V+ b1 mT=[-1 -1 1 1]; V$ Z( e1 y7 Z5 i( b
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'trainrp');& l+ c4 J- H, l7 j N- ^+ Y
net.trainParam.show=10000;; o6 _: ^/ r& V( y; @ Y p5 C
net.trainParam.lr=0.05;. |9 \6 x2 e1 ~# ?% J8 I$ k
net.trainParam.lr_inc=1.05;
" ?5 U% R; Z2 J6 F) ^net.trainParam.epochs=10000;
5 w- r6 R- {6 p! l" \1 ]6 t6 ^- pnet.trainParam.goal=1e-5*100
+ ]$ \ L+ [& P! P[net tr]=train(net,P,T);
* l k$ k: S6 j" W
- `' k8 M% o: [$ C2 L, S5：共轭梯度1
: {# r1 d6 e5 S0 w% c8 f" Lclc0 D& H4 r* z- z- Y, g# I
P=[-1 -1 2 2 ;0 5 0 5];% E7 y! E4 j4 q0 j' l. y2 d
T=[-1 -1 1 1];1 ], {6 A2 X: }3 W" M
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traincgf');4 x* ? E. T* M3 R
net.trainParam.show=10000;
& g- ` c$ [( }9 e0 Cnet.trainParam.lr=0.05;4 r/ U: g8 W, E, {# D0 z# y
net.trainParam.lr_inc=1.05;
0 h, f9 w4 `2 h4 E6 I8 `net.trainParam.epochs=10000;
' O# T. u6 h% S* w; A" c) L+ V2 Snet.trainParam.goal=1e-5*1000 E% b0 m- b2 L/ @
[net tr]=train(net,P,T);
3 ?- c' G5 A0 [8 e& P D
4 g' [. x7 z& q' y7 i6：共轭梯度2
- o: u) V1 T8 x( `6 N6 P3 K& Z6 v' tclc
6 H' m1 F) m% R+ x8 g, WP=[-1 -1 2 2 ;0 5 0 5];
" `/ d9 t8 W" i4 {T=[-1 -1 1 1];
, a# Z9 `% k( _( `" Lnet=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traincgp');
; }4 `9 f, Z4 F" n: z2 }( Xnet.trainParam.show=10000;
% a8 w! E' g( Tnet.trainParam.lr=0.05;
4 D/ [; V8 a+ ?4 Cnet.trainParam.lr_inc=1.05; q/ {0 U1 Y; ]2 e9 ], i h! d$ s
net.trainParam.epochs=10000; C& H+ @5 F$ `
net.trainParam.goal=1e-5*1000 o' ?- T: g3 Y2 l3 ?2 E+ q' _5 [3 o1 W
[net tr]=train(net,P,T);
1 a) ?9 k& |0 U: r% K) s! ?0 {1 z) R7 G# k+ }0 M
7：共轭梯度3
# k' [* L) e+ ?' q1 E0 Eclc
8 s4 H: |' ]* s: W0 m) ^P=[-1 -1 2 2 ;0 5 0 5];, w, Y, x+ ^, s5 a7 }/ A9 k
T=[-1 -1 1 1];
$ c$ A% V6 X' G% j$ j& C2 Bnet=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traincgb');
1 M# K$ |3 J6 Y! o% P- F9 _& tnet.trainParam.show=10000;
9 g) T6 s, g+ D- ^ N0 |net.trainParam.lr=0.05;; z" v8 w7 s. y& L1 X0 G2 m
net.trainParam.lr_inc=1.05;4 s. ^% n* x4 D) X0 A( o
net.trainParam.epochs=10000;- v; a( p) ~0 P. G( m. U7 ~
net.trainParam.goal=1e-5*100$ m" l2 S1 y% R
[net tr]=train(net,P,T);
' E1 {) p8 [" y: ], {
6 w- I: p5 V; U8：共轭梯度4! A2 }9 d1 r" T, e
clc E3 W/ A. f% o! z8 }
P=[-1 -1 2 2 ;0 5 0 5];: ?5 F1 e0 @+ j7 _
T=[-1 -1 1 1];
l. c! N/ `% m* Z3 Cnet=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traincgb');4 ]2 {! |+ `3 S0 |3 f3 o U; P
net.trainParam.show=10000;
. g0 R# R8 V6 x5 t: _) l+ Enet.trainParam.lr=0.05;$ C: R6 b4 _8 R2 W7 Y
net.trainParam.lr_inc=1.05;9 |7 i7 P& e1 f, a* Q/ W
net.trainParam.epochs=10000;
! K3 z7 u( o) ^$ w& m5 Xnet.trainParam.goal=1e-5*100
X* P. f" b' V4 R) F[net tr]=train(net,P,T);
; f& e) V' n7 j" M/ _) l6 h! J
+ r3 ^* \5 F' g9：拟牛顿法;* Z7 R4 D9 w' ?5 u( p
clc
|3 v9 U/ b, {- C+ X) fP=[-1 -1 2 2 ;0 5 0 5];
% X4 y6 |% Y! h5 s& WT=[-1 -1 1 1];8 f8 y6 C5 Y8 F2 d/ o/ ~
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'trainbfg');! @$ ]* I& l9 Q
net.trainParam.show=10000;
' ~7 K+ g4 M1 i8 l' Rnet.trainParam.lr=0.05;, w" |* t8 v$ L6 V5 f4 u
net.trainParam.lr_inc=1.05;& a* }0 u% s! ~2 O; H9 d- t5 U, ^7 r
net.trainParam.epochs=10000;
" X$ {% e6 K+ b% O7 a( bnet.trainParam.goal=1e-5*100/ D( a0 v% c0 ?& v+ x( k1 s4 F
[net tr]=train(net,P,T);
4 N0 \7 j/ ?! d+ m
. x5 S% A( n4 t' ~) ]0 W. \/ V10:一步正割8 M1 z% N& _9 r, n4 p0 V5 g6 b
clc
# w' D, O+ K$ c) q! ]5 nP=[-1 -1 2 2 ;0 5 0 5];! u0 S+ u1 I9 d- J) u: i
T=[-1 -1 1 1];, t. Q( i$ @$ {6 O0 [ K* o
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'trainoss');+ z9 E0 g' g2 T* N7 I# \6 Y
net.trainParam.show=10000;
3 p( ]5 V2 o/ n! l5 _( n4 g0 dnet.trainParam.lr=0.05;6 A( I: I& w7 y. _: z0 S
net.trainParam.lr_inc=1.05;9 ~1 }& m5 W, g( O4 p# J9 L
net.trainParam.epochs=10000;. Q: c! |( N0 I# q
net.trainParam.goal=1e-5*100 A$ D. H: z6 j3 T s0 P' B
[net tr]=train(net,P,T);4 ?( B) ^9 _# K1 O+ y6 Q
7 d- d% }" y1 X* t11：levenberg-marquarat:
1 V7 L' ~, p6 J5 w/ q& Zclc j0 A# C) @ i* P: {" b$ t$ C: Y
P=[-1 -1 2 2 ;0 5 0 5];
0 v. j. G* s' F% n: V8 rT=[-1 -1 1 1];
$ ?% @7 B, ?/ e% s- E( n+ T% h2 `net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'trainlm');" `. h n6 g0 m+ D
net.trainParam.show=10000;
# u2 I+ m# e2 jnet.trainParam.lr=0.05;
! p/ x9 t1 h) B% k% \3 Znet.trainParam.lr_inc=1.05;
$ b0 R7 h! p& P2 Z C) u: Y2 L# Unet.trainParam.epochs=10000;% N. p. g% i7 q: d% [4 C
net.trainParam.goal=1e-5*1002 [! \; r3 m) l+ y
[net tr]=train(net,P,T);
1 j) _ D4 h$ G F' Z7 n- p O, ~/ \! z
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发表于 2019-11-11 15:02
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支持！
反对！