How to use neural pattern recognition to create a base
newbie: How to use neural pattern recognition to create a base signal and recognizing signal.(having very little matlab experience) i am doing a project that use signals(neural,voice) to command a machine. i've heard that neural pattern recognition, matlab is able to create a database of signals and able to recognize it when a similar signal passes through the network. i have 33 samples of 1000 elements signals including 6 possible signals that i have decided to use as the base(a single command only). Also,i have gone through the GUI version of the neural pattern recognition with given sample but stuck at creating target signal (1 and 0) for my own. i need a guidance on the creating, understanding target and subsequence possible problems to proceed with my project. Thank you. *As a newbie,i do not know the codes very well.
John Williams answered .
2025-11-20
1. Use PCA to reduce the dimensionality
2. Use k-means with k=6 to separate the data into 6 classes.
3. There are many ways to obtain unbiased estimates of error rates
a. Repeat and combine results: Randomly choose 22 for training
and 11 for testing
b. Repeat and combine results: Use 3-fold cross-validation
c. For either of the above,
i. Add noise to training data and parameterize performance via SNR
ii. Add noise to test data and parameterize performance via SNR
iii. Add noise to all data and parameterize performance via SNR
I favor 1, 2, 3b, 3cii