User Reference:SpectralEstimator - Revision history

Mellinger: /* FirstBinCenter */

2025-12-22T13:08:14Z

FirstBinCenter

← Older revision		Revision as of 13:08, 22 December 2025
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	A float value representing the center of the first frequency bin, e.g. "5Hz".		A float value representing the center of the first frequency bin, e.g. "5Hz".

	In case of the AR algorithm, this is the first point where the estimated spectral function is evaluated. In case of the FFT algorithm, the input signal's DC component is shifted to the <tt>FirstBinCenter</tt> frequency by modulating with a complex carrier signal of a frequency <math>\omega = 2 \pi \texttt{FirstBinCenter}</math>.		In case of the AR algorithm, this is the first point where the estimated spectral function is evaluated. In case of the FFT algorithm, the input signal's DC component is shifted by the <tt>FirstBinCenter</tt> frequency by modulating with a complex carrier signal of a frequency <math>\omega = 2 \pi \texttt{FirstBinCenter}</math>.

	===LastBinCenter===		===LastBinCenter===

Mellinger at 12:34, 22 December 2025

2025-12-22T12:34:29Z

← Older revision		Revision as of 12:34, 22 December 2025
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	*0: spectral amplitude,		*0: spectral amplitude,
	*1: spectral power,		*1: spectral power,
	*2: AR coefficients.		*2: AR or FFT coefficients.
	If the output is a spectrum, the output signal's elements correspond to uniformly spaced frequency bins. For raw AR coefficients, the first output signal element contains total signal power, followed by the model's denominator coefficients.		If the output is a spectrum, the output signal's elements correspond to uniformly spaced frequency bins. For raw AR coefficients, the first output signal element contains total signal power, followed by the model's denominator coefficients.

Mellinger: /* EvaluationsPerBin */

2018-10-23T13:37:22Z

EvaluationsPerBin

← Older revision		Revision as of 13:37, 23 October 2018
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	===EvaluationsPerBin===		===EvaluationsPerBin===
	A single nonnegative integer value representing the number of uniformly spaced evaluation points that enter into a single bin's value.		For the AR algorithm, this is a single nonnegative integer value representing the number of uniformly spaced evaluation points that enter into a single bin's value. For the FFT algorithm, this value is ignored.

	==States==		==States==

Mellinger: /* FirstBinCenter */

2018-10-23T13:34:51Z

FirstBinCenter

← Older revision		Revision as of 13:34, 23 October 2018
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	===FirstBinCenter===		===FirstBinCenter===
	A float value representing the center of the first frequency bin, e.g. "5Hz".		A float value representing the center of the first frequency bin, e.g. "5Hz".

			In case of the AR algorithm, this is the first point where the estimated spectral function is evaluated. In case of the FFT algorithm, the input signal's DC component is shifted to the <tt>FirstBinCenter</tt> frequency by modulating with a complex carrier signal of a frequency <math>\omega = 2 \pi \texttt{FirstBinCenter}</math>.

	===LastBinCenter===		===LastBinCenter===

Mellinger: /* LastBinCenter */

2018-10-23T13:27:51Z

LastBinCenter

← Older revision		Revision as of 13:27, 23 October 2018
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	===LastBinCenter===		===LastBinCenter===
	A float value representing the center of the last frequency bin.		A float value representing the center of the last frequency bin.

			If <tt>LastBinCenter</tt> - <tt>FirstBinCenter</tt> is not an integer multiple of <tt>BinWidth</tt>, <tt>LastBinCenter</tt> is rounded downward towards the closest integer multiple of <tt>BinWidth</tt>.

	===BinWidth===		===BinWidth===

Mellinger: /* WindowLength */

2018-10-23T13:23:18Z

WindowLength

← Older revision		Revision as of 13:23, 23 October 2018
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	500ms		500ms
	5		5

			In case of the FFT algorithm, the <tt>WindowLength</tt> parameter does not determine the number of input samples in the FFT (FFT size); rather, FFT size is determined by the <tt>BinWidth</tt> parameter.

	===Detrend===		===Detrend===

Mellinger: /* BinWidth */

2018-10-23T13:20:38Z

BinWidth

← Older revision		Revision as of 13:20, 23 October 2018
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	===BinWidth===		===BinWidth===
	A single nonnegative float value representing the width of a single bin, e.g. "3Hz".		A single nonnegative float value representing the width of a single bin, e.g. "3Hz". For the AR algorithm, this is the distance between points where the spectrum is evaluated. For the FFT algorithm, this determines the number of points over which the FFT is calculated (FFT size). If the <tt>WindowSize</tt> parameter is less than FFT size, the FFT's input is padded with zeros. If <tt>WindowSize</tt> is greater than FFT size, multiple FFTs are computed, and their results summed up, until all input data has been used.

	===EvaluationsPerBin===		===EvaluationsPerBin===

Mellinger: /* Physical unit of the estimated spectrum */

2018-10-23T13:12:52Z

Physical unit of the estimated spectrum

← Older revision		Revision as of 13:12, 23 October 2018
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	In BCI2000, signal amplitude is measured in <math>\mu V</math>, so signal energy is measured in <math>(\mu V)^2</math>. Measuring frequency in Hz, and time in seconds, these will cancel out in the physical unit's denominator. Thus, the physical unit of a power spectrum is <math>(\mu V)^2</math>, and <math>\mu V</math> for an amplitude spectrum.		In BCI2000, signal amplitude is measured in <math>\mu V</math>, so signal energy is measured in <math>(\mu V)^2</math>. Measuring frequency in Hz, and time in seconds, these will cancel out in the physical unit's denominator. Thus, the physical unit of a power spectrum is <math>(\mu V)^2</math>, and <math>\mu V</math> for an amplitude spectrum.

			===Normalization of the estimated spectrum===
			Normalization is applied to energy, and chosen such that input energy per second matches output energy, summed over all bins. For an input signal <math>s_t</math> and an output spectrum <math>f_\omega</math>, this means

			<math>\frac{\sum_{t = t_0..t_N}s_t^2}{t_N - t_0} = \sum_{\omega}\|f_\omega\|^2.</math>

			Normalization is applied for both AR and FFT algorithms in this way.

	==Parameters==		==Parameters==

Mellinger: /* Physical unit of the estimated spectrum */

2018-10-22T15:52:33Z

Physical unit of the estimated spectrum

← Older revision		Revision as of 15:52, 22 October 2018
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	A power spectrum is an energy density distribution over frequencies. Thus, its physical dimension is "energy per frequency". The ARFilter actually computes a time series of such spectra, representing a flow of energy through each single point in the frequency domain. The proper physical dimension of such a flow is "energy per frequency per time".		A power spectrum is an energy density distribution over frequencies. Thus, its physical dimension is "energy per frequency". The ARFilter actually computes a time series of such spectra, representing a flow of energy through each single point in the frequency domain. The proper physical dimension of such a flow is "energy per frequency per time".

	In BCI2000, signal amplitude is measured in <math>\mu V</math>, so signal energy is measured in <math>\mu V^2</math>. Measuring frequency in Hz, and time in seconds, these will cancel out in the physical unit's denominator. Thus, the physical unit of a power spectrum is <math>\mu V^2</math>, and <math>\mu V</math> for an amplitude spectrum.		In BCI2000, signal amplitude is measured in <math>\mu V</math>, so signal energy is measured in <math>(\mu V)^2</math>. Measuring frequency in Hz, and time in seconds, these will cancel out in the physical unit's denominator. Thus, the physical unit of a power spectrum is <math>(\mu V)^2</math>, and <math>\mu V</math> for an amplitude spectrum.

	==Parameters==		==Parameters==

Mellinger at 11:04, 14 June 2012

2012-06-14T11:04:35Z

← Older revision		Revision as of 11:04, 14 June 2012
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	==Function==		==Function==<!--TODO update-->
	The SpectralEstimator computes a continually updated estimate of the spectrum of its input data, i.e. the distribution of amplitude or energy over frequencies.		The SpectralEstimator computes a continually updated estimate of the spectrum of its input data, i.e. the distribution of amplitude or energy over frequencies.
	Spectral estimation is done separately for each of the filter's input channels.		Spectral estimation is done separately for each of the filter's input channels.