Rank: 1893 based on 61 downloads (last 30 days) and 2 files submitted
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Magnus Norgaard

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14 Apr 2003 nnctrl The NNCTRL toolkit is a set of tools for design and simulation of neural network based control syste Author: Magnus Norgaard fuzzy logic, neural networks, nonlinear control, systems, inverse control, predictiv 32 9
  • 3.4
3.4 | 20 ratings
14 Apr 2003 Screenshot nnsysid The NNSYSID toolbox contains a number of tools for identification of nonlinear dynamic systems with Author: Magnus Norgaard fuzzy logic, neural networks, system, identfication, nonlinear, toolbox 29 17
  • 4.05263
4.1 | 20 ratings
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22 Nov 2013 nnctrl The NNCTRL toolkit is a set of tools for design and simulation of neural network based control syste Author: Magnus Norgaard Smart, Mr

05 Jul 2013 nnsysid The NNSYSID toolbox contains a number of tools for identification of nonlinear dynamic systems with Author: Magnus Norgaard fabian

I contact you to ask you to please help me with the tool, after having the trained network as the selected model structure or network is exported to Simulink. thanks

11 Oct 2011 nnctrl The NNCTRL toolkit is a set of tools for design and simulation of neural network based control syste Author: Magnus Norgaard Ali, Elsayed Hassan

this files very imprtant

09 Oct 2011 nnsysid The NNSYSID toolbox contains a number of tools for identification of nonlinear dynamic systems with Author: Magnus Norgaard Smart, Mr

25 Jul 2011 nnsysid The NNSYSID toolbox contains a number of tools for identification of nonlinear dynamic systems with Author: Magnus Norgaard Amir

I have a problem in running the toolbox nnsysid. Actually I got the following messeges,If anyone knows the answer, then I would appreciate.

[w1,w2] = wrescale('nnoe',W1,W2,uscales,yscales,NN);
>> [thd,trv,fpev,tev,deff,pv] = ...
nnprune('nnoe',NetDef,W1,W2,u1s,y1s,NN,trparms,prparms,u2s,y2s);
Warning: Matrix is close to singular or badly scaled.
Results may be inaccurate. RCOND = 1.639375e-016.
> In nnprune at 372

Network training started.

iteration # 1 W = 5.571e-002
iteration # 2 W = 4.712e-002
iteration # 3 W = 4.314e-002
iteration # 4 W = 3.508e-002
iteration # 5 W = 3.186e-002
iteration # 6 W = 2.975e-002
iteration # 7 W = 2.947e-002
iteration # 8 W = 2.904e-002
iteration # 9 W = 2.889e-002
iteration # 10 W = 2.883e-002
iteration # 11 W = 2.880e-002
iteration # 12 W = 2.869e-002
iteration # 13 W = 2.864e-002
iteration # 14 W = 2.863e-002
iteration # 15 W = 2.862e-002
iteration # 16 W = 2.859e-002
iteration # 17 W = 2.858e-002
iteration # 18 W = 2.855e-002
iteration # 19 W = 2.855e-002
iteration # 20 W = 2.853e-002
iteration # 21 W = 2.853e-002
iteration # 22 W = 2.852e-002
iteration # 23 W = 2.851e-002
iteration # 24 W = 2.850e-002
iteration # 25 W = 2.850e-002
iteration # 26 W = 2.849e-002
iteration # 27 W = 2.849e-002
iteration # 28 W = 2.849e-002
iteration # 29 W = 2.848e-002
iteration # 30 W = 2.848e-002
iteration # 31 W = 2.848e-002
iteration # 32 W = 2.848e-002
iteration # 33 W = 2.848e-002
iteration # 34 W = 2.847e-002
iteration # 35 W = 2.847e-002
iteration # 36 W = 2.847e-002
iteration # 37 W = 2.847e-002
iteration # 38 W = 2.846e-002
iteration # 39 W = 2.846e-002
iteration # 40 W = 2.846e-002
iteration # 41 W = 2.845e-002
iteration # 42 W = 2.845e-002
iteration # 43 W = 2.845e-002
iteration # 44 W = 2.845e-002
iteration # 45 W = 2.844e-002
iteration # 46 W = 2.844e-002
iteration # 47 W = 2.844e-002
iteration # 48 W = 2.844e-002
iteration # 49 W = 2.844e-002
iteration # 50 W = 2.843e-002

Network training ended.

Network training started.

??? Error using ==> nnoe
AN ERROR OCCURED IN A CMEX-PROGRAM

Error in ==> nnprune at 257
[W1,W2,dummy1,dummy2,dummy3] = nnoe(NetDef,NN,W1,W2,trparmsp,Y,U);

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