Performance Evaluation of Machine Learning‐Based Channel Equalization Techniques: New Trends and Challenges
Wireless communication systems have evolved and offered more smart and advanced
systems like ad hoc and sensor‐based infrastructure fewer networks. These networks are …
systems like ad hoc and sensor‐based infrastructure fewer networks. These networks are …
Challenges and prospects of machine learning in visible light communication
Visible light communication (VLC) is a promising research field in modern wireless
communication. VLC has its irreplaceable strength including rich spectrum resources, no …
communication. VLC has its irreplaceable strength including rich spectrum resources, no …
Application of Legendre neural network for solving ordinary differential equations
S Mall, S Chakraverty - Applied Soft Computing, 2016 - Elsevier
In this paper, a new method based on single layer Legendre Neural Network (LeNN) model
has been developed to solve initial and boundary value problems. In the proposed …
has been developed to solve initial and boundary value problems. In the proposed …
Functional link adaptive filters for nonlinear acoustic echo cancellation
D Comminiello, M Scarpiniti… - … on Audio, Speech …, 2013 - ieeexplore.ieee.org
This paper introduces a new class of nonlinear adaptive filters, whose structure is based on
Hammerstein model. Such filters derive from the functional link adaptive filter (FLAF) model …
Hammerstein model. Such filters derive from the functional link adaptive filter (FLAF) model …
Non-linear channel equalization using modified grasshopper optimization algorithm
KK Ingle, RK Jatoth - Applied Soft Computing, 2024 - Elsevier
In this paper, a modified grasshopper optimization algorithm is proposed for equalization of
non-linear wireless communication channels. Even though grasshopper optimisation …
non-linear wireless communication channels. Even though grasshopper optimisation …
Nonlinear system identification using a cuckoo search optimized adaptive Hammerstein model
An attempt has been made in this paper to model a nonlinear system using a Hammerstein
model. The Hammerstein model considered in this paper is a functional link artificial neural …
model. The Hammerstein model considered in this paper is a functional link artificial neural …
An efficient JAYA algorithm with lévy flight for non-linear channel equalization
KK Ingle, RK Jatoth - Expert Systems with Applications, 2020 - Elsevier
Neural network (NN) based equalizers are known to outperform the linear equalizers based
on finite impulse response (FIR) adaptive filter for highly dispersive and non-linear channels …
on finite impulse response (FIR) adaptive filter for highly dispersive and non-linear channels …
Nearest Kronecker product decomposition based linear-in-the-parameters nonlinear filters
SS Bhattacharjee, NV George - IEEE/ACM Transactions on …, 2021 - ieeexplore.ieee.org
A linear-in-the-parameters nonlinear filter consists of a functional expansion block, which
expands the input signal to a higher dimensional space nonlinearly, followed by an adaptive …
expands the input signal to a higher dimensional space nonlinearly, followed by an adaptive …
Application of Bat algorithm and its modified form trained with ANN in channel equalization
P Kumar Mohapatra, S Kumar Rout, S Kishoro Bisoy… - Symmetry, 2022 - mdpi.com
The transmission of high-speed data over communication channels is the function of digital
communication systems. Due to linear and nonlinear distortions, data transmitted through …
communication systems. Due to linear and nonlinear distortions, data transmitted through …
Nonlinear channel equalization for wireless communication systems using Legendre neural networks
In this paper, we present a computationally efficient neural network (NN) for equalization of
nonlinear communication channels with 4-QAM signal constellation. The functional link NN …
nonlinear communication channels with 4-QAM signal constellation. The functional link NN …