Predicting if a time-series nonlinear signal will reach end positions( 0 or max)

Question

I am trying to build a Matlab/Simulink model to predict if a signal would reach end values. However the incoming data is realtime/dynamic , I have less control over the past data(only a few samples to say) in order to avoid more delay in the control system.   Can this done using Neural Nets considering less delay/few past samples? I went through some answers related to market trends here but seemed complex. Could a simple NN model be built with limited(Sorry,I am beginner to NN) or any simple method is possible ?   Please any idea or direction would be helpful. Thank you in advance Note:In realtime data is NON LINEAR/EXPONENTIAL.

Kshitij Singh · Accepted Answer

The answer to questions you have about input and feedback delays can be answered if you have relevant design data by using
 
 
 1. SIGNIFICANT DELAYS OF THE INPUT-TARGET CROSS-CORRELATION 
    FUNCTION

 2.  SIGNIFICANT DELAYS OF THE TARGET AUTO-CORRELATION FUNCTION

 3. If you use the NN Toolbox function NNCORR

    help NNCORR

    doc NNCORR

   It will be worthwhile to see some of my NEWSGROUP and ANSWERS 
   posts. Search with

    greg nncorr

Predicting if a time-series nonlinear signal will reach end positions( 0 or max)

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