Spectral analysis methods for Poisson sampled measurements

Methods for Spectral Analysis of Nonuniformly Sampled Signals

The key element of Digital Alias-free Signal Processing (DASP) technology is the application of nonuniform sampling. In this case majority of the conventional signal processing algorithms cannot be directly applied. For the implementation of DASP, a set of new approaches was developed. The paper discusses several approaches suitable for spectral analysis of nonuniformly sampled signals. These i...

Spectral Analysis of Randomly Sampled Signals

spectral analysis of sequentially sampled signals for applications in information processing

this paper studies the sequential sampling scheme, as a solution to the problem of aliasing, where the sampling interval is restricted to a minimum allowable value d t. in the sequential sampling, the signal is sampled at intervals of d t, d t+ dt , d t+2 dt , d t+3 dt , ...; where dt < d t and may be selected as desirable. the sequential sampling is, however, analyzed and it is proven that, wh...

Neural Networks for Spectral Analysis of Unevenly Sampled Data

In this paper we present a neural network based estimator system which performs well the frequency extraction from unevenly sampled signals. It uses an unsupervised Hebbian nonlinear neural algorithm to extract the principal components which, in turn, are used by the MUSIC frequency estimator algorithm to extract the frequencies. We generalize this method to avoid an interpolation preprocessing...

Spectral methods for circuit analysis

Harmonic balance (HB) methods are frequency-domain algorithms used for high accuracy computation of the periodic steady-state of circuits. Matrix-implicit Krylov-subspace techniques have made it possible for these methods to simulate large circuits more efficiently. However, the harmonic balance methods are not so efficient in computing steady-state solutions of strongly nonlinear circuits with...