It is known that one-dimensional Dirac systems with potentials q which tend to −∞ (or ∞) at infinity, such that 1/q is of bounded variation, have a purely absolutely continuous spectrum covering the whole real line. We show that, for the system on a half-line, there are no local maxima of the spectral density (points of spectral concentration) above some value of the spectral parameter if q sat...

In this article, we report that the origins of 1/f noise in pm-Si:H film resistors are inhomogeneity and defective structure. The results obtained are consistent with Hooge's formula, where the noise parameter, αH, is independent of doping ratio. The 1/f noise power spectral density and noise parameter αH are proportional to the squared value of temperature coefficient of resistance (TCR). The ...

We derive simplified formulas for analyzing the stability of stochastic parametrically forced linear systems. This extends the results in [2] where, assuming the stochastic excitation is small, the stability of such systems was computed using a weighted sum of the extended power spectral density over the eigenvalues of the unperturbed operator. In this paper, we show how to convert this to a su...

Nonlinearity estimation and spectral regrowth prediction are crucial to power amplifier linearization. The correlation techniques shown here can estimate amplifier nonlinearity and predict out-of-band power spectrum. Crosscorrelation is performed between the output envelope and a test sequence generated from the input signal and can be carried out in background during amplifier operations. The ...

In speech enhancement, noise power spectral density (PSD) estimation plays a key role in determining appropriate de-nosing gains. In this paper, we propose a robust noise PSD estimator for binaural speech enhancement in timevarying noise environments. First, it is shown that the noise PSD can be numerically obtained using an eigenvalue of the input covariance matrix. A simplified estimator is t...

Many multi-channel dereverberation and noise reduction techniques such as the multi-channel Wiener filter (MWF) require an estimate of the late reverberation and noise power spectral densities (PSDs). State-of-the-art multi-channel methods for estimating the late reverberation PSD typically assume that the noise PSD matrix is known. Instead of assuming that the noise PSD matrix is known, in thi...

6. Spectral Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Random processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Random variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Random vectors . . . . . . . . . . ....