Improvements in the channel Equalizer Performance Using Modified LMS and BP Algorithms

In this paper, the performance of SAFFIRE algorithm is inspected in comparison with non-iterative weighted minimum norm estimate (wMNE) method, for both MEG

Instead of frequency domain, channel can be estimated in time-domain by DFT-based approach, whose performance is better and complexity is less than LSE and LMMSE.. The

This example is used to compare the performance of the proposed technique with the Gauss-TD separation algorithm in [18] and the adaptive spline neural network (ASNN)

O objetivo deste estudo é apresentar o processo de formação ética por meio da disciplina Humanidades Médicas do curso de medicina de instituição de ensino superior do Sul do

Received: 27 June 2020; Accepted: 29 July 2020; Published: 2 August 2020



Abstract: Given the need for comparative research on the participation of adolescents

Among the techniques based NN, recurrent neural network (RNN) [4][5] proposed to solve the nonlinear channel equalization problem, RNN have shown better performance than

The computer simulation reveals that the proposed system gives better BER performance compared to Multilevel Space Time Trellis Coded Modulation (ML STTCM) over fast fading

It is observed that the proposed technique has better probability of correct timing detection performance compared to the existing algorithm, in all the UWB channel models proposed