HOW CAN I USE 3 DIFFERENT DATA TO TRAIN NEURAL NETWORK

I am trying to train a neural network with raw data, normalised data and standardised data.But it shows some errors. I need to do this as one after another resulting 3 different neural networks so I can compare the output with the target.

The code I tried is attached below,

%training neural network using raw data

p=x
p

p = p'

t=t'

mynet = feedforwardnet

view(mynet)

train = train(mynet,p,t)

results = sim(mynet,p)

compare = t==results

%training data using standardised data

p1=xs

p1

p1=p'

t1=t'

mynet1 = feedforwardnet

view(mynet1)

train = mynet1(mynet1,p1,t1)

results1 = sim(mynet1,p)

compare1 = t1==results1

%training data using normaised data

p2=xn

p2

p2=p'

t2=t'

mynet2 = feedforwardnet

view(mynet2)

train2 = mynet2(mynet2,p2,t2)

results2 = sim(mynet2,p2)

compare2 = t2==results2

and the error message I hae recieved

>> train = mynet1(mynet1,p1,t1)

Error using network/sim (line 248)

Inputs is not a matrix or cell array.

[JIBIN GEORGE]

found out the answer mysef...just had to transpose as

p1=p1'

and

p2=p2'

[JIBIN GEORGE]

still has some more errors

[Srivardhan Gadila]

@JIBIN GEORGE, can you provide the exact information of the other errors you are getting apart from the ones mentioned in the question.