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Journal ArticleDOI

An unwindowed RLS adaptive lattice algorithm

John M. Cioffi
- 01 Mar 1988 - 
- Vol. 36, Iss: 3, pp 365-371
TLDR
A covariance-RLS lattice adaptive-filtering algorithm that permits nonzero initial conditions and need not 'warn' N-1 iterations in advance of the first iteration to preserve its low computational requirements is presented.
Abstract
A covariance-RLS lattice adaptive-filtering algorithm is presented. The algorithm permits nonzero initial conditions and need not 'warn' N-1 iterations in advance of the first iteration to preserve its low computational requirements. These are both improvements over previous lattice algorithms. The algorithm also has a slight computational advantage over previous solutions, rendering it more applicable to adaptive-filtering applications such as fast-starting adaptive equalizers and echo cancellers, where the initial data in the adaptive filter are not, and cannot be assumed to be, zero. >

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Citations
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Journal ArticleDOI

Adaptive filtering for non-Gaussian stable processes

TL;DR: A large class of physical phenomena observed in practice exhibit non-Gaussian behavior, and the /spl alpha/-stable distributions, which have heavier tails than Gaussian distributions, are considered to model non- Gaussian signals.
Journal ArticleDOI

Tracking improvements in fast RLS algorithms using a variable forgetting factor

TL;DR: The concept of a variable forgetting factor (VFF) is incorporated into fast recursive least-squares (FRLS) algorithms and the bias introduced by the use of the VFF is analyzed.
Proceedings ArticleDOI

Adaptive filtering approaches for non-Gaussian stable processes

TL;DR: In this paper, /spl alpha/-stable distributions, which have heavier tails than Gaussian distribution, are considered to model non-Gaussian signals.
Journal ArticleDOI

A new unwindowed lattice filter for RLS estimation

TL;DR: Adaptive lattice algorithms are derived for the solution of unwindowed least squares estimation problems for AR and FIR models to embed the unwindowing problem in a larger prewindowed problem and then eliminate superfluous terms in the lattice.
Journal ArticleDOI

Digital data over video channels: Techniques for Spacelab

TL;DR: In this paper, various techniques for transmitting digital data over a composite video channel were examined, with a view to transmitting data from experiments on the Space Shuttle orbiter, with the goal to transmit data from the STS-120 data collection mission.
References
More filters
Journal ArticleDOI

Adaptive equalization

TL;DR: In this article, the authors give an overview of the current state of the art in adaptive equalization and discuss the convergence and steady-state properties of least mean square (LMS) adaptation algorithms.

Adaptive equalization

TL;DR: This tutorial paper gives an overview of the current state of the art in adaptive equalization and discusses the convergence and steady-state properties of least mean-square (LMS) adaptation algorithms, including digital precision considerations, and three classes of rapidly converging adaptive equalizer algorithms.
Journal ArticleDOI

Adaptive Maximum-Likelihood Receiver for Carrier-Modulated Data-Transmission Systems

TL;DR: A uniform receiver structure for linear carrier-modulated data-transmission systems is derived which for decision making uses a modified version of the Viterbi algorithm, which operates directly on the output signal of a complex matched filter and requires no squaring operations.
Journal ArticleDOI

Fast, recursive-least-squares transversal filters for adaptive filtering

TL;DR: Fast transversal filter (FTF) implementations of recursive-least-squares (RLS) adaptive-filtering algorithms are presented in this paper and substantial improvements in transient behavior in comparison to stochastic-gradient or LMS adaptive algorithms are efficiently achieved by the presented algorithms.
Journal ArticleDOI

Tracking properties and steady-state performance of RLS adaptive filter algorithms

TL;DR: This paper treats analytically and experimentally the steady-state operation of RLS (recursive least squares) adaptive filters with exponential windows for stationary and nonstationary inputs and presents new RLS restart procedures applied to transversal structures for mitigating the disastrous results of the third source of noise.
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