• References Introduction This paper presents an overview of operator adjustable equalizers in the professional audio industry. The term “operator adjustable equalizers” is no doubt a bit vague and cumbersome. For this, the author apologizes. Needed was a term to differentiate between fixed equalizers and variable equalizers. Fixed equalizers, such as pre-emphasis and de-emphasis circuits, phon...

A signal su ers from nonlinear, linear, and additive distortion when transmitted through a channel. Linear equalizers are commonly used in receivers to compensate for linear channel distortion. As an alternative, nonlinear equalizers have the potential to compensate for all three sources of channel distortion. Previous authors have shown that nonlinear feedforward equalizers based on either mul...

The steady-state performance of adaptive equalizers can significantly vary when they are implemented in finite precision arithmetic, which makes it vital to analyze their performance in a quantized environment. In this paper we present a fixed point analysis for the steady-state mean square error (MSE) of a blind adaptive equalizer and the optimal value of the step-size that minimizes this MSE....

Constrained adaptive optimization techniques are employed in this paper to design direct blind equalizers. The method is based on minimizing the equalizer's output variance subject to appropriate constraints. The constraints are chosen to guarantee no desired signal cancellation and are also jointly and recursively optimized to improve performance. Our method provides adaptive solutions which d...

1.1 Background In ordinary channel equalizer and multi-antenna system, many types of detecting methods have been proposed to compensate the distorted signals or recover the original symbols of the desired user [1]-[3]. For channel equalization, transversal equalizers (TEs) and decision feedback equalizers (DFEs) are commonly used as a detector to compensate the distorted signals [2]. It is well...

This paper proposes a novel adaptive decision feedback equalizer (DFE) based on self-constructing recurrent fuzzy neural network (SRFNN) for quadrature amplitude modulation systems. Without the prior knowledge of channel characteristics, a novel training scheme containing both selfconstructing learning and back-propagation algorithms is derived for the SRFNN. The proposed DFE is compared with s...

Decision feedback equalizers are commonly employed to reduce the error caused by intersymbol interference. Here, an adaptive decision feedback equalizer is presented with a new adaptation algorithm. The algorithm follows a block-based approach of normalized least mean square (NLMS) algorithm with set-membership filtering and achieves a significantly less computational complexity over its conven...

This paper describes and compares the different approaches most commonly used for power spectrum estimation in continuous-time linear adaptive equalizers based on the conventional feedback scheme for Gbps digital communications. In addition, a new equalization approach based on the feedforward topology is proposed. As an example, simulation results demonstrate some advantage of feedforward agai...

Neural networks add flexibility to the design of equalizers for digital communications. In this work novel decisionfeedback (DF) neural equalizers (DFNE) are introduced and compared with classical DF equalizers and Viterbi demodulators. It is shown that the choice of a cost functional based on the Discriminative Learning (DL), coupled with a fast training paradigm, can provide neural equalizers...