Blind equalizers avoid the transmission of pilot sequences, allowing a more efficient use of
the channel bandwidth. Normally, after a first rough equalization is achieved, it is necessary …

This chapter provides an introduction to adaptive signal processing, covering basic
principles through the most important recent developments. After a brief example for, we …

This paper reports a solution to a linear blind equalizer used in communication systems
under the effect of two factors: i) An unknown linear inter symbol interference and ii) the …

It is well known that constant-modulus-based algorithms present a large mean-square error
for high-order quadrature amplitude modulation (QAM) signals, which may damage the …

In this paper, we propose a numerically robust blind equalization scheme to mitigate
cochannel and intersymbol interferences and separate signals from a convolutive mixture in …

In the literature, we can find several blind adaptive deconvolution algorithms based on
closed-form approximated expressions for the conditional expectation (the expectation of the …

In a blind adaptive deconvolution problem, the convolutional noise observed at the output of
the deconvolution process, in addition to the required source signal, is—according to the …

The performance of blind equalization algorithm is closely related to the characteristics of
the channel. Eigenvalue spread of the channel can reflect the influence of the channel on …

In this paper, we design and analyze a Newton-like blind equalization algorithm for the
APSK system. Specifically, we exploit the principle of minimum entropy deconvolution and …

Recently, a new blind adaptive deconvolution algorithm was proposed based on a new
closed-form approximated expression for the conditional expectation (the expectation of the …