Hello,

I'm working on speech recogntion using some kind of neural networks.

I'm trying LVQ function in matlab Newlvq for 300 utterance (10 words,

10 speaker,3 repetition) for training and the same for test.

The problem is in testing the function sim may produce empty matrix

for one or more utterance , they can't recognize the utterance at

all , as we know neural try to find the nearest class for the

utterance , but in many cases it causes empty matrix.

What's the problem ? How can overcome this?

Thanks in advance

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2. Neural Network Architecture with MATLAB Neural Network Toolbox

Dear neural network experts,

I would like to make a neural network model for a situation

when some of the input variables can interact, while

others don't have any interactions. This information is

based on logical considerations and I have to include it

into the architecture of the net.

For example, I have 3 different groups of input variables.

Within each groups the variables are disjunct (i.e. no

interaction). Variables of different groups may interact.

This would result in either

- restrictions to some weights of a network consisting of

completely inter-linked neurons (i.e. some weights have

to be zero), or

- a combination of neural networks, one for each group of

variables and one combining the groups (nested nets?).

This network needs to be created, trained and simulated.

How can I implement this based on commands of the neural network

toolbox (newff?, trainlm?)?

I would be very happy if you can point me to an example or

similar that demonstrates how the commands have to be used

in this situation.

Many thanks in advance!

Steffen

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