Abstract:
Noise-like signal components are detected within arbitrary regions of the time-frequency plane. Various transforms are applied to G time domain samples with different spectral/temporal resolutions. The flatness of the time domain samples and the frequency samples for each transform are compared. If the computed flatness measures are about the same, the samples are assumed to be noisy. Noise-like signal components can be detected using a general filterbank within a limited time interval and frequency range by decomposing the signal into N subbands. To each group of G subband samples in time {tk}, a linear orthogonal transform is applied to obtain the frequency domain samples {fi}. The flatness of the time domain samples is compared to the flatness of the frequency domain samples {fi}. A filterbank with uniform frequency-tiling can be used to detect noise-like signal components. To detect noise with a bandwidth of a given noise detection partition, two linear transforms are applied to the coefficients within the partition. A linear orthogonal synthesis transform is applied over frequency and a linear orthogonal analysis transform is applied over time in a noise detection partition to yield coefficients with maximum time and frequency resolution {tk} and {fi}, respectively. The flatness of the time domain samples {tk} and the frequency domain samples {fi} are compared to decide whether the frequency noise detection partition is noise-like. Noise with a non-flat spectrum can be detected by preprocessing the signal according to its inverse spectral envelope before detecting noise-like signal components with a non-flat spectral/temporal envelope.