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Gaussian Noise Stimulus Generation

This is a stimulus generation class in which each tonotopic bin is filled with amplitude chosen from a Gaussian distribution. This class can work with binned representations of the signals.

Unique Properties

This stimulus generation class has two properties in addition to those inhereted from the Abstract and Abstract Binned classes. Defaults:

amplitude_mean = -10 % Mean of the Gaussian from which the amplitude is chosen
amplitude_var = 3 % Variance of the Gaussian from which the amplitude is chosen

generate_stimulus

[stim, Fs, spect, binned_repr, frequency_vector] = generate_stimulus(self)

Generate a stimulus vector of length self.nfft+1. Bins are filled with an amplitude value chosen randomly. from a Gaussian distribution.

OUTPUTS:

stim: self.nfft + 1 x 1 numerical vector, the stimulus waveform,

Fs: 1x1 numerical scalar, the sample rate in Hz.

spect: self.nfft / 2 x 1 numerical vector, the half-spectrum, in dB.

binned_repr: self.n_bins x 1 numerical vector, the binned representation.

frequency_vector: self.nfft / 2 x 1 numerical vector, the frequencies associated with the spectrum, in Hz.

Class Properties Used:

- n_bins
- amplitude_mean
- amplitude_var