[[abstract]]The authors propose a Bernoulli-Gaussian model based maximum-likelihood channel equalizer, which is a fixed-lag block signal detection algorithm, for binary channels in the presence of intersymbol interference and additive white Gaussian noise. The proposed equalizer not only performs as well as the maximum-likelihood sequence estimator via Viterbi algorithm but also allows the channel length to be infinite, and its computational load and storage are linearly rather than exponentially proportional to block size[[fileno]]2030157030080[[department]]電機工程學
Codelength based inference is used to decode binary symbols distorted by an inter-symbol interferenc...
In this paper, novel statistical sampling based equalization techniques and CNN based detection are ...
This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) m...
Abstract-Based on a modifled Bernoulli-Gaussian model, we propose an adaptive maximum-likelihood cha...
[[abstract]]Based on a modified Bernoulli-Gaussian model, we propose an adaptive maximum-likelihood ...
[[abstract]]The paper proposes a recursive single-most-likely-replacement (SMLR) equaliser, that is ...
We consider the design of a linear equalizer with a finite number of coefficients in the context of ...
This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) mo...
We present a family of equalizers and targets for certain inter-symbol interference (ISI) channels w...
In 1972, Forney proposed a maximum likelihood sequence estimator for digital PAM (pulse amplitude mo...
This paper presents new detector that is used to mitigate intersymbol interference introduced by ban...
In 2002, Skoglund, Giese and Parkvall introduced a novel concept of combining channel estimation, eq...
This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) mo...
In high speed digital transmission over bandlimited channels, one of the principal impairments, besi...
The maximum a posteriori probability (MAP) criterion for channel equalisation has been used with the...
Codelength based inference is used to decode binary symbols distorted by an inter-symbol interferenc...
In this paper, novel statistical sampling based equalization techniques and CNN based detection are ...
This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) m...
Abstract-Based on a modifled Bernoulli-Gaussian model, we propose an adaptive maximum-likelihood cha...
[[abstract]]Based on a modified Bernoulli-Gaussian model, we propose an adaptive maximum-likelihood ...
[[abstract]]The paper proposes a recursive single-most-likely-replacement (SMLR) equaliser, that is ...
We consider the design of a linear equalizer with a finite number of coefficients in the context of ...
This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) mo...
We present a family of equalizers and targets for certain inter-symbol interference (ISI) channels w...
In 1972, Forney proposed a maximum likelihood sequence estimator for digital PAM (pulse amplitude mo...
This paper presents new detector that is used to mitigate intersymbol interference introduced by ban...
In 2002, Skoglund, Giese and Parkvall introduced a novel concept of combining channel estimation, eq...
This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) mo...
In high speed digital transmission over bandlimited channels, one of the principal impairments, besi...
The maximum a posteriori probability (MAP) criterion for channel equalisation has been used with the...
Codelength based inference is used to decode binary symbols distorted by an inter-symbol interferenc...
In this paper, novel statistical sampling based equalization techniques and CNN based detection are ...
This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) m...