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In this paper we present an optimized DSP implementation of a modified error-feedback lattice least-square (EF-LSL) adaptive filtering algorithm. Simple measures that provide numerical stability for poor persistent excitation are also proposed. As a result of the optimization and the stability measures, an efficient and stable implementation of a fast… (More)

We propose blind equalization algorithms that perform similarly to supervised ones, independently of the QAM order. They converge approximately to the Wiener solution, which generally provides a relatively low misadjustment. Besides presenting strategies to speed up their convergences, we provide sufficient conditions for the stability of the symbol-based… (More)

— Blind equalization algorithms with good convergence and tracking properties and numerical robustness are desired to ensure the good performance of communications systems. In this paper, we present transient and steady-state analyses for the dual-mode constant modulus algorithm (DM-CMA), a version of CMA that avoids its well-known divergence problem. We… (More)

We address the problem of signal separation using space-time blind equalization techniques. A novel blind algorithm, denoted ACMA (Accelerated Constant Modulus Algorithm), is proposed. It minimizes the constant modulus cost function and is based on a tuner used in adaptive control that sets the second derivative (" acceleration ") of the coefficient… (More)

The performance of two minimal QR-LSL algorithms in a low precision environment is investigated. For both algorithms backward consistency and backward stability become guaranteed under simple numerical conventions. They present stable behavior even when excited with ill conditioned signals such as predictable signals. Since the problem of ensuring numerical… (More)

The efficient separation of signals is a frequent problem in multiuser communication systems. Among many algorithms to blind deconvolution of a multiple-input multiple-output (MIMO) systems, the one that utilizes higher-order cumulants has advantages in regards of convergence rate. Inspired on this algorithm and on a stochastic gradient approach , we… (More)