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1:一般模式的BP:
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P=[-1 -1 2 2 ;0 5 0 5];
2 ]/ Y; N, b: q2 N; NT=[-1 -1 1 1];
9 ]1 R! u0 Y& X! c2 wnet=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traingd');
0 S( Z8 q; l" [' P& x$ ~' O* Mnet.trainParam.show=50;& @& q& v; D$ ]2 X; G! Q( d8 O3 F
net.trainParam.lr=0.05;
% D* d$ \" [* q0 b9 Unet.trainParam.epochs=300;3 P- b: N s0 ]: a; a( s
net.trainParam.goal=1e-5
4 o' \1 Q! H' R' J- E1 {[net tr]=train(net,P,T);. Y7 D5 Q+ Z; G$ P; ^0 R/ F
% j& Y0 I+ V3 R/ U2 t2：加入动量的BP. z7 l$ t; g1 p; X5 k; t
clc
- K+ }) \! }) j1 I" hP=[-1 -1 2 2 ;0 5 0 5];
" [' A4 X. H5 d. N V5 s: x9 b- ]T=[-1 -1 1 1];
' v: q2 z/ K: I$ Lnet=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traingdm');
! h. D E! V4 j* L) D$ g$ Inet.trainParam.show=10000;, p: E m2 g5 g' b& E* D
net.trainParam.lr=0.05;
7 p5 c. t' } Mnet.trainParam.mc=0.9;
) |* g& F- u8 B vnet.trainParam.epochs=10000;
$ _4 b1 h9 B; X/ ynet.trainParam.goal=1e-5*100* C0 A! a( E$ H
[net tr]=train(net,P,T);" r8 X; u3 T1 J1 T w. a! I
$ @0 c0 D5 o5 B/ b1 V2 B2 N/ @
3：自适应LR变步长：
; B4 |6 G- a( A7 ~ l5 iclc
% p+ P# u( X4 \ @P=[-1 -1 2 2 ;0 5 0 5];
6 i" L- b) i5 M$ X* `T=[-1 -1 1 1];, i# |% E( D- u( G; ^
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traingda');$ A! [ E! s4 T5 c+ A, V
net.trainParam.show=10000;* |; [! X. k5 G3 O+ M6 h& K) I# Y
net.trainParam.lr=0.05;0 Y# S+ H, K% W9 @. f
net.trainParam.lr_inc=1.05;8 D+ ~. `4 Q' c4 A {
net.trainParam.epochs=10000; ]+ H! e+ m# ^
net.trainParam.goal=1e-5*100
, ^( |7 ?2 C8 b[net tr]=train(net,P,T);
3 G* p* j. _2 R5 A' h& d
/ V: z' ^- q" e# B3 e E% o3 {: p! e2 v: G! r9 p
4：弹性梯度法
- P9 D6 G/ i2 F; nclc$ r. Y8 O5 F7 w' j S2 t
P=[-1 -1 2 2 ;0 5 0 5];/ m$ z* A. ?1 ?6 i8 w! n) j4 J4 q
T=[-1 -1 1 1];: R2 a/ a. E5 K! P' v
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'trainrp');
# m* X l" q% R Y7 gnet.trainParam.show=10000;
+ v) ~/ a9 C V3 J) t1 Snet.trainParam.lr=0.05;# p w( b& i% a0 d- q; Y$ ~
net.trainParam.lr_inc=1.05;2 o5 q) \9 c3 f: l. }
net.trainParam.epochs=10000;8 `8 d( ~ ~' \5 P c
net.trainParam.goal=1e-5*100
6 `6 V; @, s& O4 t) }4 g, s. j[net tr]=train(net,P,T);% e$ c- i, x: k! c' G
! b8 w9 v2 w, |0 E1 @& V
5：共轭梯度1, b3 Q. f9 _) D( a
clc; X" z/ z: U* u! s5 Z2 H
P=[-1 -1 2 2 ;0 5 0 5];( @1 L+ z2 v' N' ]. Z
T=[-1 -1 1 1];
1 T1 x; B. ^: bnet=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traincgf');, z' A$ g5 z6 @% T2 q; K$ {! a
net.trainParam.show=10000;# d* v X* v' k: k
net.trainParam.lr=0.05;
+ ^) v" t' v5 P& Znet.trainParam.lr_inc=1.05;! r% H3 b n! ?7 W. v% N
net.trainParam.epochs=10000; E& F2 e+ b! o$ O3 \" W. p
net.trainParam.goal=1e-5*100; o) N+ N, x q' f" E
[net tr]=train(net,P,T);+ v! J8 n, d3 Q' U. T
- j* @& w% L4 b y c
6：共轭梯度24 a! B9 S; N" w
clc
+ S2 ^0 |2 h: x" N) q2 CP=[-1 -1 2 2 ;0 5 0 5];
# q2 }# Q. L- R- G9 a% JT=[-1 -1 1 1];& v* N) G" f) w! x5 _
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traincgp');9 h: r* g i. ]5 D+ S/ u% T' U' Z& n
net.trainParam.show=10000;8 o; K5 J4 f$ e' p/ U8 I% O4 x! @
net.trainParam.lr=0.05;
3 [$ ^# C7 ]* _net.trainParam.lr_inc=1.05;
: H! q; ^5 m" G Qnet.trainParam.epochs=10000;
" {8 l+ \. {5 K- c7 A1 d) _$ ~net.trainParam.goal=1e-5*100
" L$ t. E! Q+ F6 D' {4 |[net tr]=train(net,P,T);0 ^ G% V7 o& N& f" r7 j
1 [- v8 L7 y% F% H/ l1 i' X7 ?, \; b7：共轭梯度3
' f$ q: Y$ i6 a, m) fclc4 x \% h' B7 a% N) A
P=[-1 -1 2 2 ;0 5 0 5]; L' r; J2 G/ f
T=[-1 -1 1 1];4 R! h9 Z/ q4 E" }' Q7 y
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traincgb');5 Z2 p8 @. L, N# e
net.trainParam.show=10000;6 B% `- f' V, D u) r$ b) a
net.trainParam.lr=0.05;
) e1 n0 J, D6 _net.trainParam.lr_inc=1.05;
9 D6 o k6 i- q( [6 L: vnet.trainParam.epochs=10000;
5 ^, c# z0 `- mnet.trainParam.goal=1e-5*100
( o' J+ U, \/ J$ K. Q[net tr]=train(net,P,T);- [! [# f% S' U4 E' @) x/ T
& h3 U2 p- `& B' B j
8：共轭梯度40 {2 ^7 b$ ^0 r0 t+ V
clc' C& m, l; j" d1 g4 O7 _# S
P=[-1 -1 2 2 ;0 5 0 5];
" A! U% P, J! t1 s3 c* ^T=[-1 -1 1 1];
4 z! F: |# Y4 ^( L: ynet=newff(minmax(P),[3 ,1],{'tansig','purelin'},'traincgb'); j: }1 A: C, ?# p0 ^' s4 D
net.trainParam.show=10000;1 B4 }( V/ ?# F' i6 H# a
net.trainParam.lr=0.05;
" q ~5 a+ I7 _$ s% }1 h d- }) knet.trainParam.lr_inc=1.05;
2 i2 t6 h( J9 ~net.trainParam.epochs=10000;% S5 M) j, O( I
net.trainParam.goal=1e-5*100! i* D$ J1 G2 _! r
[net tr]=train(net,P,T);
, n, ]+ }( \, j) g+ j% c
: p/ g- y: x" }/ J0 @3 q9：拟牛顿法;
_4 G Z# E( k/ G- X% H2 aclc
9 V* ~% F4 I3 [/ AP=[-1 -1 2 2 ;0 5 0 5];8 T1 B9 y5 Z9 R3 h3 ~
T=[-1 -1 1 1];4 m; e K/ q2 E, a# r n: I
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'trainbfg');+ i+ p3 G0 W- S7 U! z1 T
net.trainParam.show=10000;* h9 v& q- z# z T
net.trainParam.lr=0.05;
. q ~4 I& R: x9 {net.trainParam.lr_inc=1.05;' P+ j' G. k- ^
net.trainParam.epochs=10000;
6 I4 a" Y! o6 p8 ~& }7 jnet.trainParam.goal=1e-5*1002 n- {# Y. ]7 X8 `& i8 F
[net tr]=train(net,P,T);+ z" `1 C" p2 ?/ H) T+ @
$ W! x) Q9 y0 a- s; M& \
10:一步正割
" \/ C' D" D+ }5 b6 w5 nclc2 X0 _0 k9 e. f8 _
P=[-1 -1 2 2 ;0 5 0 5];
! J- W' s! P( A) Q) HT=[-1 -1 1 1];4 L; f# \. q* i- x+ V
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'trainoss');
' _! _1 l# |" Y7 a" A( Gnet.trainParam.show=10000;6 M5 B1 {7 A2 o
net.trainParam.lr=0.05;
) m) v$ K% p* X; r* w4 ]0 x' Enet.trainParam.lr_inc=1.05;
1 ~) M0 b7 q) O, knet.trainParam.epochs=10000;
; k. I/ L" [, e( I. b8 L) s1 M+ Anet.trainParam.goal=1e-5*100
) A% d' s% x8 P V* J( i, A _! y[net tr]=train(net,P,T);
. s5 f* k# I, B4 L7 q6 ?6 k* I* Q" B+ l1 w! X3 \3 ~/ M
11：levenberg-marquarat:8 o; J! S) q4 M0 R: M4 _8 j
clc
) W7 n" t/ W. v; b, T2 k8 U4 w) {0 Z5 DP=[-1 -1 2 2 ;0 5 0 5];0 ^8 I# z5 K; A
T=[-1 -1 1 1];2 K0 I- Q( y3 G3 V! y
net=newff(minmax(P),[3 ,1],{'tansig','purelin'},'trainlm');; [9 w8 x1 ^9 q/ U# z5 p0 [
net.trainParam.show=10000;
1 o. a! S$ W% ]+ F0 a0 _# inet.trainParam.lr=0.05;
* r! K, x" l- s/ ?net.trainParam.lr_inc=1.05;
o3 b3 b% E' |: m& @% f# J, vnet.trainParam.epochs=10000;
I. I6 Q% [% f* @; z2 bnet.trainParam.goal=1e-5*100
8 V3 n: S0 |% t7 |/ C4 q. }[net tr]=train(net,P,T);
4 D# x: M, p0 h ^3 W2 j. M, H" m- ^5 y2 q0 X, R! u9 D5 ?
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发表于 2019-11-11 15:02
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支持！
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