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Variance Example
Description:
Demonstrates the use of Basic Math and Support Functions to calculate the variance of an input sequence with N samples. Uniformly distributed white noise is taken as input.
Algorithm:
The variance of a sequence is the mean of the squared deviation of the sequence from its mean.
This is denoted by the following equation:
 variance = ((x[0] - x') * (x[0] - x') + (x[1] - x') * (x[1] - x') + ... + * (x[n-1] - x') * (x[n-1] - x')) / (N-1)
where, x[n] is the input sequence, N is the number of input samples, and x' is the mean value of the input sequence, x[n].
The mean value x' is defined as:
 x' = (x[0] + x[1] + ... + x[n-1]) / N
Block Diagram:
Variance.gif
Variables Description:
  • testInput_f32 points to the input data
  • wire1, wir2, wire3 temporary buffers
  • blockSize number of samples processed at a time
  • refVarianceOut reference variance value
CMSIS DSP Software Library Functions Used:

Refer arm_variance_example_f32.c