I have a pressure sensor and depending on the pressure applied resistance is measured between 2 points of the 3 electrodes connected to it.That is either between electrodes1 and 2 with 2 being ground or2 and 3 with 3 being ground or3 and 1 with 1 being ground The pressure is applied at 2 positions on the sensor (position A and B)[the points of pressure are chosen at random within A or B during a measurement cycle. which means it remains same during a cycle but changes in the next cycle]This are the set of measurements I had done1. Measured R12, R23, R13
- (12(ground) No Pressure)
- (23(ground) No Pressure)
- (31(ground) No Pressure)
2. While applying pressure on random point on A, measured R12, R23, R13
- (12(ground) Pressure on A )
- (23(ground) Pressure on A )
- (31(ground) Pressure on A )
2. While applying pressure on random point on B, measured R12, R23, R13
- (12(ground) Pressure B )
- (23(ground) Pressure on B )
- (31(ground) Pressure on B )
This setup was run for 52 cyclesI want to make an NN pattern…
Hi Maysam,
It is not very clear what types of labels you are try to classify in your experiment. Or is it classification problem?
Hi, thank you for the question you asked. Yes, this classification has a typographical problem, for example, it should contain 13 characters
- (12(ground) Pressure on A )
- (23(ground) Pressure on A )
- (31(ground) Pressure on A )
- (13ground) Pressure on A )
Hi
Are you using a classifier to classify 13 different classes? And what they are for example? How did you devided your data for training and testing?
Define number of classes, number of target outputs, decide which classifier then train 70%,15%, 15 % verify matrix.
If number of test signals are less present each one and classify.
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