In an uncoupled parallel array of bistable dynamical elements subject to a common noisy subthreshold rectangular signal, the signal-to-noise ratio (SNR) gain can be improved by tuning the internally added array noise. A SNR gain above unity is observed in certain regions of the array noise intensity. The maximum SNR gain is obtained as the size of the array goes to infinity. This form of stocha...

This paper presents an advanced speaker verification system using wavelet transforms. The conventional signal processing techniques assume the signal to be stationary and are ineffective in recognizing non stationary signals such as voice signals. Voice signals which are more dynamic could be analysed with far better accuracy using wavelet transform. The developed voice verification system is w...

In an adaptive generalized sidelobe canceler interference signals are canceled when the reference inputs, or auxiliary beams, contain information about those interference signals while not containing information about the mainlobe signal of interest. Assuming a wide sense stationary scenario, the behavior and performance of this adaptive system approach the behavior and performance of the corre...

Estimation of power spectra is a central question in signal analysis and its applications such as Geophysics. This is classical for stationary signals for which the power spectral density, i.e. the Fourier transform of the covariance, is deened as a function of the frequency only. In the general case, signals under study are not stationary. This work has been motivated by signals obtained in th...

random number generation is one of the human abilities. it is proven that the sequence of random numbers generated by people do not follow full randomness criteria. these numbers produced by brain activity seem to be completely non stationary. in this paper, we show that there is a distinction between the random numbers generated by different people who provides the discrimination capability, a...

Effective feature extraction for robust speech recognition is a widely addressed topic and currently there is much effort to invoke non-stationary signal models instead of quasi-stationary signal models leading to standard features such as LPC or MFCC. Joint amplitude modulation and frequency modulation (AM-FM) is a classical non-parametric approach to nonstationary signal modeling and recently...

This paper introduces a Modified Error Data Normalized Step Size (MEDNSS) algorithm in which time varying step size depends upon normalization of both error and data vector. An Adaptive Noise Canceller (ANC) is used to improve the system performance in the presence of signal leakage components or signal crosstalk. This ANC consists of three microphones and two adaptive filters that automaticall...

A least-squares linear fixed-interval smoothing algorithm is derived to estimate signals from uncertain observations perturbed by additive white noise. It is assumed that the Bernoulli variables describing the uncertainty are only correlated at consecutive time instants. The marginal distribution of each of these variables, specified by the probability that the signal exists at each observation...

We present a low complexity speech enhancement technique for real-life multi-source environments. Assuming that the speaker identity is known a priori, we present the idea of incorporating speaker model to enhance a target signal corrupted in non-stationary noise in a reverberant scenario. Based on experiments, this helps to improve the limited performance of noise-tracking based speech enhance...

Digital stochastic measurement method implementation is considered from signal stationarity point of view. It is shown how conceptual block diagram for digital stochastic measurement of one Fourier coefficient can be simplified and used for developing conceptual block diagram for measuring predefined set of signal harmonics. Hardware of digital stochastic measurement block interfaced to recordi...