Impulsive Noise Parameter Estimation: A Deep CNN-LSTM Network Approach

2021 ◽  
Author(s):  
Alka Isac ◽  
Bassant Selim ◽  
Zeinab Sobhanigavgani ◽  
Georges Kaddoum ◽  
Mallik Tatipamula
Keyword(s):  
Parameter Estimation ◽  
Impulsive Noise ◽  
Network Approach ◽  
Noise Parameter ◽  
Deep Cnn ◽  
Lstm Network

CSVC-Net: Code-Switched Voice Command Classification using Deep CNN-LSTM Network

2021 ◽  
Author(s):  
Arowa Yasmeen ◽  
Fariha Ishrat Rahman ◽  
Sabbir Ahmed ◽  
Md. Hasanul Kabir
Keyword(s):  
Voice Command ◽  
Deep Cnn ◽  
Lstm Network

scholarly journals An inverse POD-RBF network approach to parameter estimation in mechanics

2012 ◽  
Vol 20 (5) ◽  
pp. 749-767 ◽  
Author(s):  
Craig A. Rogers ◽  
Alain J. Kassab ◽  
Eduardo A. Divo ◽  
Ziemowit Ostrowski ◽  
Ryszard A. Bialecki
Keyword(s):  
Parameter Estimation ◽  
Network Approach ◽  
Rbf Network

Parameter Estimation Based on Fractional Correlation under Alpha-Stable Distribution Noise Environment in Bistatic MIMO Radar System

2014 ◽  
Vol 989-994 ◽  
pp. 3710-3713
Author(s):  
Li Li
Keyword(s):  
Parameter Estimation ◽  
Stable Distribution ◽  
Impulsive Noise ◽  
Mimo Radar ◽  
Radar System ◽  
Noise Model ◽  
Distribution Model ◽  
Music Algorithm ◽  
Bistatic Mimo Radar ◽  
Noise Environment

This paper takes the-stable distribution as the noise model and works on the parameter estimation problem of bistatic Multiple-Input Multiple-Output (MIMO) radar system in the impulsive noise environment.This paper presents a signal model and a novel method for parameter estimation in bistatic MIMO radar system in the impulsive noise environment. Firstly, a signal array model is constructed based on the-stable distribution model. Secondly, Doppler parameters are jointly estimated by searching the optimal rotation angle to meet concentrated-energy of the FLOS-FC. Furthermore, two algorithms are presented for the estimation of DODs and DOAs, including based on FLOS-MUSIC algorithm and FLOS-ESPRIT algorithm. Simulation results are presented to verity the effectiveness of the proposed method.

K-clutter plus noise parameter estimation using fractional positive and negative moments

2016 ◽  
Vol 52 (2) ◽  
pp. 960-967 ◽  
Author(s):  
Amar Mezache ◽  
Izzeddine Chalabi ◽  
Toufik Laroussi ◽  
Mohamed Sahed
Keyword(s):  
Parameter Estimation ◽  
Noise Parameter ◽  
Negative Moments
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