Spline adaptive filtering algorithm based on Heaviside step function

2022 ◽  
Author(s):  
Sihai Guan ◽  
Qing Cheng ◽  
Yong Zhao ◽  
Bharat Biswal
Keyword(s):  
Adaptive Filtering ◽  
Step Function ◽  
Heaviside Step Function ◽  
Filtering Algorithm

scholarly journals Unscented Particle Filter Algorithm Based on Divide-and-Conquer Sampling for Target Tracking

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2236
Author(s):  
Sichun Du ◽  
Qing Deng
Keyword(s):  
Particle Filter ◽  
State Space ◽  
Adaptive Filtering ◽  
Divide And Conquer ◽  
Particle Swarm Algorithm ◽  
Tracking Accuracy ◽  
Filtering Algorithm ◽  
Maneuvering Target ◽  
Unscented Particle Filter ◽  
Particle Filter Algorithm

Unscented particle filter (UPF) struggles to completely cover the target state space when handling the maneuvering target tracing problem, and the tracking performance can be affected by the low sample diversity and algorithm redundancy. In order to solve this problem, the method of divide-and-conquer sampling is applied to the UPF tracking algorithm. By decomposing the state space, the descending dimension processing of the target maneuver is realized. When dealing with the maneuvering target, particles are sampled separately in each subspace, which directly prevents particles from degeneracy. Experiments and a comparative analysis were carried out to comprehensively analyze the performance of the divide-and-conquer sampling unscented particle filter (DCS-UPF). The simulation result demonstrates that the proposed algorithm can improve the diversity of particles and obtain higher tracking accuracy in less time than the particle swarm algorithm and intelligent adaptive filtering algorithm. This algorithm can be used in complex maneuvering conditions.

scholarly journals Robust Adaptive Filtering Algorithm for Self-Interference Cancellation with Impulsive Noise

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 196
Author(s):  
Jun Lu ◽  
Qunfei Zhang ◽  
Wentao Shi ◽  
Lingling Zhang ◽  
Juan Shi
Keyword(s):  
Adaptive Filtering ◽  
Interference Cancellation ◽  
Impulsive Noise ◽  
Weight Vector ◽  
Filtering Algorithm ◽  
Convergence Performance ◽  
Simulation Results ◽  
Robust Adaptive ◽  
Arctangent Cost Function ◽  
Simultaneous Transmission

Self-interference (SI) is usually generated by the simultaneous transmission and reception in the same system, and the variable SI channel and impulsive noise make it difficult to eliminate. Therefore, this paper proposes an adaptive digital SI cancellation algorithm, which is an improved normalized sub-band adaptive filtering (NSAF) algorithm based on the sparsity of the SI channel and the arctangent cost function. The weight vector is hardly updated when the impulsive noise occurs, and the iteration error resulting from impulsive noise is significantly reduced. Another major factor affecting the performance of SI cancellation is the variable SI channel. To solve this problem, the sparsity of the SI channel is estimated with the estimation of the weight vector at each iteration, and it is used to adjust the weight vector. Then, the convergence performance and calculation complexity are analyzed theoretically. Simulation results indicate that the proposed algorithm has better performance than the referenced algorithms.

A Meshless Local Petrov-Garlerkin Method for Solving the Biharmonic Equation

2014 ◽  
Vol 931-932 ◽  
pp. 1488-1494
Author(s):  
Supanut Kaewumpai ◽  
Suwon Tangmanee ◽  
Anirut Luadsong
Keyword(s):  
Relative Error ◽  
Biharmonic Equation ◽  
Interpolation Method ◽  
Step Function ◽  
Special Treatment ◽  
Maximum Relative Error ◽  
Heaviside Step Function ◽  
Treatment Techniques ◽  
Point Interpolation Method ◽  
Point Interpolation

A meshless local Petrov-Galerkin method (MLPG) using Heaviside step function as a test function for solving the biharmonic equation with subjected to boundary of the second kind is presented in this paper. Nodal shape function is constructed by the radial point interpolation method (RPIM) which holds the Kroneckers delta property. Two-field variables local weak forms are used in order to decompose the biharmonic equation into a couple of Poisson equations as well as impose straightforward boundary of the second kind, and no special treatment techniques are required. Selected engineering numerical examples using conventional nodal arrangement as well as polynomial basis choices are considered to demonstrate the applicability, the easiness, and the accuracy of the proposed method. This robust method gives quite accurate numerical results, implementing by maximum relative error and root mean square relative error.

A Novel Two Dimensional Adaptive Filtering Algorithm for Image De-Noising via Fractional Gradient

2017 ◽  
Vol 11 (3) ◽  
pp. 21-30 ◽  
Author(s):  
Syed Sajjad Hussain Rizvi ◽  
Jawwad Ahmad ◽  
Muhammad Zubair ◽  
Shamim Akhtar
Keyword(s):  
Adaptive Filtering ◽  
Two Dimensional ◽  
Filtering Algorithm
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