Partial linearization methods in nonlinear programming
Journal of Optimization Theory and Applications
Discrete-time signal processing (2nd ed.)
Discrete-time signal processing (2nd ed.)
Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Noise amplification of periodic nonuniform sampling
IEEE Transactions on Signal Processing
Use of the symmetrical number system in resolving single-frequencyundersampling aliases
IEEE Transactions on Signal Processing
Aliasing of polynomial-phase signal parameters
IEEE Transactions on Signal Processing
Filterbank reconstruction of bandlimited signals from nonuniformand generalized samples
IEEE Transactions on Signal Processing
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For discrete time systems, the sampling rate is an important design issue. On the one hand, a sampling rate below the Nyquist rate results in spectral aliasing, on the other hand, a sampling rate chosen higher than necessary increases the computational burden. We show in this paper that aliased spectra, arising from sampling a random process below the Nyquist rate, may be completely eliminated. We show that a deterministic or random waveform that is sampled at a rate less than the classical Nyquist rate may be successfully reconstructed if two arbitrarily closely spaced samples are retained each sampling instant. A convergence proof is given for the random waveform case. We suggest a diagonally loaded maximum likelihood estimator approach to reduce the reconstruction errors resulting from timing jitter between the pairs of impulse samples as an area of future research.