Estimates the frequency of a given sine wave of unknown frequency using the Buneman algorithm.
Length of each set of data. The node performs computation for each set of data.
sample length must be greater than zero.
This input is available only if you wire a double-precision, floating-point number to x.
Default: 100
Error conditions that occur before this node runs.
The node responds to this input according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
Default: No error
The frequency estimation of the sine wave that the sampled signal represents. This output is the index of the maximum frequency and a noninteger.
Error information.
The node produces this output according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
If an underlying time signal is not exactly periodic with period n, where n denotes the size of the data array, you can use the Buneman algorithm to calculate the unknown frequency 0 ≤ f_{0} ≤ f_{1} ≤ f_{2} ≤ f_{3} < 0.5f_{s}.
The following formula describes the Buneman algorithm:
where b is the frequency and F_{b} is the value of the Fourier transform of the input signal X at b. You can determine the value of b using the greatest value of $\left|{F}_{b}\left(\text{X}\right)\right|$.
The formula for β is exact for pure sine waves and a good estimation in all other cases.
Where This Node Can Run:
Desktop OS: Windows
FPGA: This product does not support FPGA devices