Spectral Estimation Using Improved Recursive Least Square (RLS) Algorithm: An Investigational Study

2015 ◽  
pp. 363-376
Author(s):  
Kantipudi M. V. V. Prasad ◽  
H. N. Suresh
Keyword(s):  
Spectral Estimation ◽  
Least Square ◽  
Recursive Least Square ◽  
Rls Algorithm

scholarly journals RSS Based Wi-Fi Positioning Method Using Recursive Least Square (RLS) Algorithm

2018 ◽  
Vol 7 (2.24) ◽  
pp. 492
Author(s):  
Sreevardhan Cheerla ◽  
D Venkata Ratnam
Keyword(s):  
Least Square ◽  
Recursive Least Square ◽  
Rls Algorithm ◽  
Positioning Systems ◽  
Indoor Location ◽  
Positioning Method ◽  
Accurate Position ◽  
Software And Hardware ◽  
Newton Raphson ◽  
Raphson Method

Due to rapid increase in demand for services which depends upon exact location of devices leads to the development of numerous Wi-Fi positioning systems. It is very difficult to find the accurate position of a device in indoor environment due to substantial development of structures. There are many algorithms to determine the indoor location but they require expensive software and hardware. Hence receiving signals strength (RSS) based algorithms are implemented to find the self-positioning. In this paper Newton-Raphson, Gauss-Newton and Steepest descent algorithms are implemented to find the accurate location of Wi-Fi receiver in Koneru Lakshmaiah (K L) University, Guntur, Andhra Pradesh, India. From the results it is evident that Newton -Raphson method is better in providing accurate position estimations. 

Adaptive Order Tracking Technique Using Recursive Least-Square Algorithm

2002 ◽  
Vol 124 (4) ◽  
pp. 502-511 ◽  
Author(s):  
Mingsian R. Bai ◽  
Jihjau Jeng ◽  
Chingyu Chen
Keyword(s):  
Least Square ◽  
Recursive Least Squares ◽  
Frequency Resolution ◽  
Shaft Speed ◽  
Recursive Least Square ◽  
Rls Algorithm ◽  
Tracking Technique ◽  
Order Tracking ◽  
Conventional Methods ◽  
Bandpass Signals

Order tracking technique is one of the important tools for diagnosis of rotating machinery. Conventional methods of order tracking are primarily based on Fourier analysis with reference to shaft speed. Resampling is generally required in the fast Fourier transform (FFT)-based methods to compromise between time and frequency resolution for varying shaft speeds. Conventional methods suffer from a number of shortcomings. In particular, smearing problems arise when closely spaced orders or crossing orders are present. Conventional methods also are ineffective for the applications involving multiple independent shaft speeds. This paper presents an adaptive order tracking technique based on the Recursive Least-Squares (RLS) algorithm to overcome the problems encountered in conventional methods. In the proposed method, the problem is treated as the tracking of frequency-varying bandpass signals. Order amplitudes can be calculated with high resolution by using the proposed method in real-time fashion. The RLS order tracking technique is applicable whether it is a single-axle or multi-axle system.

scholarly journals On Modelling and Comparative Study of LMS and RLS Algorithms for Synthesis of MSA

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Ahmad Kamal Hassan ◽  
Adnan Affandi
Keyword(s):  
Worked Examples ◽  
Analytical Framework ◽  
Least Square ◽  
Least Mean Square ◽  
Recursive Least Square ◽  
Rls Algorithm ◽  
Contour Plots ◽  
Comprehensive Comparison ◽  
Artificial Neural Network Ann ◽  
Spread Factor

This paper deals with analytical modelling of microstrip patch antenna (MSA) by means of artificial neural network (ANN) using least mean square (LMS) and recursive least square (RLS) algorithms. Our contribution in this work is twofold. We initially provide a tutorial-like exposition for the design aspects of MSA and for the analytical framework of the two algorithms while our second aim is to take advantage of high nonlinearity of MSA to compare the effectiveness of LMS and that of RLS algorithms. We investigate the two algorithms by using gradient decent optimization in the context of radial basis function (RBF) of ANN. The proposed analysis is based on both static and adaptive spread factor. We model the forward side or synthesis of MSA by means of worked examples and simulations. Contour plots, 3D depictions, and Tableau presentations provide a comprehensive comparison of the two algorithms. Our findings point to higher accuracies in approximation for synthesis of MSA using RLS algorithm as compared with that of LMS approach; however the computational complexity increases in the former case.

scholarly journals Adaptive PID Controller Using RLS for SISO Stable and Unstable Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Rania A. Fahmy ◽  
Ragia I. Badr ◽  
Farouk A. Rahman
Keyword(s):  
Pid Controller ◽  
Reference Model ◽  
Least Square ◽  
Recursive Least Square ◽  
Actual System ◽  
Rls Algorithm ◽  
Controlled System ◽  
Unstable Systems ◽  
Model Computer ◽  
Slowly Vary

The proportional-integral-derivative (PID) is still the most common controller and stabilizer used in industry due to its simplicity and ease of implementation. In most of the real applications, the controlled system has parameters which slowly vary or are uncertain. Thus, PID gains must be adapted to cope with such changes. In this paper, adaptive PID (APID) controller is proposed using the recursive least square (RLS) algorithm. RLS algorithm is used to update the PID gains in real time (as system operates) to force the actual system to behave like a desired reference model. Computer simulations are given to demonstrate the effectiveness of the proposed APID controller on SISO stable and unstable systems considering the presence of changes in the systems parameters.

scholarly journals Algoritma Adaptif Sistem Downlink Menggunakan Recursive Least Square (RLS)

2017 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Agus Basukesti ◽  
Bangga Dirgantara
Keyword(s):  
Global Positioning System ◽  
Least Square ◽  
Positioning System ◽  
Recursive Least Square ◽  
Rls Algorithm ◽  
Advantages And Disadvantages ◽  
The Earth ◽  
Global Positioning ◽  
Downlink System ◽  
Simulation Results

GPS (Global Positioning System) is the popular system for navigation which assistance 32 satellites orbiting the earth. Currently, tracking positions using the Global Positioning System (GPS) is one of the best positioning tracking methods. However, GPS has a lot o f noise, so filters are needed to handle with noise on GPS. In this research, the simulation is done to extract data from GPS sensors using RLS algorithm. From the results o f identification and simulation, it can be concluded that the algorithm works well and need to analyze the advantages and disadvantages to be implemented on the downlink system designed. From the simulation results obtained that error estimation is convergent that is the longer the smaller.

Efficient Recursive Least Square Technique for Spectrum Sensing in Cognitive Radio Networks

2019 ◽  
Vol 15 (2) ◽  
pp. 1-14
Author(s):  
Bommidi Sridhar ◽  
Srinivasulu Tadisetty
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Spectral Estimation ◽  
Primary User ◽  
Least Square ◽  
Electromagnetic Spectrum ◽  
Recursive Least Square ◽  
Spectrum Utilization ◽  
Overall Performance

Cognitive radio-based systems rely on spectrum sensing techniques to detect whitespaces to exploit. Cognitive radio (CR) is an attractive approach to face the shortage in the electromagnetic spectrum resources and improve the overall spectrum utilization. However, Energy detectors perform far from optimally by affecting the performance of the underlying system. In this article, two spectrum-sensing techniques are considered for CR networks; one based on energy detection and the other based on multi-taper spectral estimation (MSE). This article proposes a new method to optimize the overall performance in cooperative spectrum sensing in cognitive radio (CR) networks. An efficient recursive least square (ERLS)-based approach is proposed in order to optimize the overall performance to monitor the primary user active or inactive stage with use of secondary user while receiving data. An energy detector (ED) and multi-taper (MTM) spectrum sensing techniques are examined as local spectrum sensing techniques. Finally, a genetic algorithm is compared with the proposed system to show the system effectiveness.

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