Improve NN performance and prediction error

I've been stuck on a homework question for a while now. The question is as follows:

Design a feed forward multi-layer neural network to approximate the function y=sin(x1)+cos(x2).

Here, -5<x1<5 and 0<x2<5. Please use x1 = (rand(1,50)-0.5)*10; x2 = rand(1,50)*5; to get the samples to train the neural network. Finally, please draw the prediction error series y - ynet for the inputs x1=-5:0.1:5 and x2=0:0.05:5.

My code is as follows. I get keep getting large prediction errors for unkknown dataset "input". Please help

x1 = (rand(1,50)-0.5)*10       %training sample one
x2 = rand(1,50)*5;              %training sample two
x = [x1;x2];
y=sin(x1)+cos(x2);              %targeted output
%feed-forward neural network with one hidden layer
%hidden layer has 10 hidden neurons
%10000 epochs training cycles, stops training when the...
%error is less or equal to 1e-25/ after 10000 epochs
%hidden neurons use a tan sigmoid activation function
%output neurons use a linear activation function
%learning rate = 0.01
%Levenberg-Marquad back-propogation is used
%***********************************************************
net = newff(minmax(x),[10 1],{'tansig','purelin'},'trainlm');
net.trainparam.epochs = 10000;
net.trainparam.goal = 1e-25;
net.trainparam.lr = 0.02;
net = train(net,x,y);
%************************************************************
input1 = -5:0.1:5;          %first input
input2 = 0:0.05:5;          %2nd input
input = [input1;input2];
y=sin(input1)+cos(input2);
ynet = net(input);
plot(y-ynet)                %error series plot
title('Error series plot')
grid

[Mohammad Sami]

Have you tried adding more hidden layers ?

[Ande Mandoyi]

Yes, does the code look fine though?