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In [1], Restrepo and Bovik developed an elegant mathematical framework in which they studied locally monotonic regressions in RN . The drawback is that the complexity of their algorithms is exponential in N. In this paper, ...

To separate and recover multiple signals in data communications, antenna arrays and acoustic sensor arrays, the impulse responses of multiple-input/multiple-output (MIMO) channels have to be identified explicitly or ...

Constrained regression problems appear in the context of optimal nonlinear filtering, as well as in a variety of other contexts, e.g., chromatographic analysis in chemometrics and manufacturing, and spectral estimation. ...

In two recent papers [1], [2], Sidiropoulos et al. have obtained statistical proofs of Maximum A Posteriori} (MAP) optimality and strong consistency of certain popular classes of Morphological filters, namely, Morphological ...

In most low-power VLSI designs, the supply voltage is usually reduced to lower the total power consumption. However, the device speed will be degraded as the supply voltage goes down. In order to meet the low-power/high-throughput ...

Baud-rate blind equalization algorithms may converge to undesirable stable equilibria due to different reasons. One is the use of FIR filter as an equalizer. It is proved in this paper that this kind of local minima exist ...

In this paper we propose a new parameter estimation algorithm for damped sinusoidal signals. Parameter estimation for damped sinusoidal signals with additive white noise is a problem of significant interests in many signal ...

A simple, linear, system model is presented for a lathe with a toolpost that incorporates active vibration suppression. The toolpost model is built from linear dynamic models of the component parts of the toolpost design: ...

This paper investigates adaptive blind equalization for multiple- input and multiple-output (MIMO) channels and its application to blind separation of multiple signals received by antenna arrays in communication systems. ...

Data is often stored in summarized form, as a histogram of aggregates (COUNTs,SUMs, or AVeraGes) over specified ranges. Queries regarding specific values, or ranges different from those stored, cannot be answered exactly ...