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31

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x = [1 0 1 1 1 0 1 1]

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1. > 8 x

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P = 1:0.05:10;

T = P*2 - 10;

Pseq = con2seq(P); Tseq = con2seq(T);

net = newelm ( P, T, 10, {'tansig', 'purelin'}) net.trainparam.goal = 0.001; net.trainparam.epochs = 2000;

net = train(net, Pseq, Tseq); Y = sim(net, Pseq);

P1 = [2 3 4 10 12 11 11.5 14]; P1seq=con2seq(P1);

sim(net, P1seq)

2. ( 8 x -

) ).

p1 = sin(1:20); % JE:^@a Z>:;9UIaU@a ?@ZU>C

t1 = ones(1,20); % >;JCIH<W> JE:^9Z9 Z>:;9UIaU9Z9 ?@ZU>C<, :IAU> 9W@U@lI

p2 = p1 * 2; % W:<Z@a Z>:;9UIaU@a ?@ZU>C

t2 = t1 * 2; % >;JCIH<W> JE:^9Z9 Z>:;9UIaU9Z9 ?@ZU>C<, :IAU> WA9;

p = [p1 p2 p1 p2]; % AEYH9: AD9W< t = [t1 t2 t1 t2]; % AEYH9: lICEa Pseq = con2seq(p);

Tseq = con2seq(t);

net = newelm (Pseq, Tseq, 10, {'tansig', 'purelin'}, 'traingdx');

net.trainparam.goal = 0.01; net.performfcn = 'sse'; net.trainparam.epochs = 1000;

[net, tr] = train(net, Pseq, Tseq); subplot(3, 1,1); semilogy(tr.epoch, tr.perf);

title('o9;@CY@ ;E:EBI'); xlabel('pJ9D@'); a = sim(net, Pseq);

time = 1:length(p); subplot(3, 1,2);

% figure(2);

36

plot(time, t, '--', time, cat(2, a{:}))

title(']EF<CGH>H HE?H<A>UUV ;E:EBI'); xlabel('T>?'); ylabel('-- - F>W>UI FU>TEUUV, - - A@DIW ;E:EBI');

p3 = p1 * 1.6;

t3 = t1 * 1.6;

p4 = p1 * 1.2;

t4 = t1 * 1.2;

pg = [p3 p4 p3 p4]; tg = [t3 t4 t3 t4]; pgseq = con2seq(pg); subplot(3, 1,3);

a = sim(net, pgseq);

plot(time, tg, '--', time, cat(2, a{ : } ) ) title(']EF<CGH>H HE?H<A>UUV ;E:EBI W9AICGU@a ?@ZU>C'); xlabel('T>?'); ylabel('---F>W>UI FU>TEUUV, -- A@DIW ;E:EBI');

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P=rands(2,1000); plot(P(1,:), P(2,:), '+') net = newsom(P, [4 5]); net.trainparam.epochs=1000; net.trainparam.show=100; net=train(net,P);

% a=sim(net,P) hold on

plotsom(net.IW{1, 1}, net.layers{1}.distances);

Testdata = rands(2,10);

Testres = vec2ind(sim(net, Testdata)) plot(Testdata(1,:), Testdata(2,:), '*k')

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