Answer by IVlad for Normalization of inputs of a feedforward Neural network
You should normalize each feature independently. column 1 represents linear regression of the last n samples, column 2 represents the average of the last n samples, column 3 represents the local max...
View ArticleAnswer by mabe for Normalization of inputs of a feedforward Neural network
You should normalise each vector/column of your matrix individually, they represent different data types and shouldn't be mixed up together. You could for example transpose your matrix to have your 3...
View ArticleAnswer by Divakar for Normalization of inputs of a feedforward Neural network
If you want to have a range of [0,1] for all the columns that normalized within each column, you can use mapminmax like so (assuming A as the 2D input array) - out = mapminmax(A.',0,1).' You can also...
View ArticleNormalization of inputs of a feedforward Neural network
Let's say I have a mxn matrix of different features of a time series signal (column 1 represents linear regression of the last n samples, column 2 represents the average of the last n samples, column...
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