Analysis of adaptive algorithms for digital beamforming in Smart Antennas

Prasad, Anurag Shivam; Vasudevan, Sandeep; Selvalakshmi, R; Ram, K Sree; Subhashini, G.; Sujitha, S.; Narayanan, B Sabarish

doi:10.1109/icrtit.2011.5972418

Cited by 20 publications

(9 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the research paper [5], authors have proposed a digital adaptive algorithm. Authors have discussed about ANN for smart weighing systems [6,7].…”

Section: Introductionmentioning

confidence: 99%

Correction of Load Cell Output using Particle Swarm Optimization

Debnath,

Sarkar,

Chakraborty

et al. 2019

IJEAT

View full text Add to dashboard Cite

A load cell is a type of force transducers that transform force and mechanical stress into electrical signal. But the output becomes distorted due to the presence of transient response. Particle Swarm Optimization (PSO) based correction of load cell output is presented this paper. PSO is a robust stochastic optimization technique that considers a swarm of particle (data) as its search space and looks for the best solution. The current approach optimizes a load cell output based on the median value of the signal. The optimization algorithm tries to bring the output response near to the median value.

show abstract

“…In the research paper [5], authors have proposed a digital adaptive algorithm. Authors have discussed about ANN for smart weighing systems [6,7].…”

Section: Introductionmentioning

confidence: 99%

Correction of Load Cell Output using Particle Swarm Optimization

Debnath,

Sarkar,

Chakraborty

et al. 2019

IJEAT

View full text Add to dashboard Cite

show abstract

“…The main beam is then directed toward the specific user, while the nulls are adjusted toward the interferers. Similarly, there are many methods and algorithms to update the array weights, each with its speed of convergence and required processing time [3]. The smart antenna system can be divided mainly into three parts.…”

Section: Amentioning

confidence: 99%

“…Thus, r can be expressed as [7]. Subsequently the direction vector   D which gives the new conjugate direction toward the optimum weights is given by [3].…”

Section: Aw D mentioning

confidence: 99%

“…The LMS Algorithm changes the weight vector along the direction of the estimated gradient based on the steepest descent method [3].The weight vector updating for LMS Algorithm is given by…”

Section: A Klms Techniquementioning

confidence: 99%

“…The weight updates equation of the Kalman based normalised RLS [3] is given below, According to Error Vector   n  eq (7), weights update   qv is the autocorrelation function of the state noise.…”

Section: B Krls Techniquementioning

confidence: 99%

See 2 more Smart Citations