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Design of Least Mean Square Algorithm for Adaptive Noise Canceller

issuu.com/iserp/docs/12.ijaest-vol-no-5-issue-no-2-de...
This paper describes the concept of adaptive noise cancelling, an alternative method of estimating signals corrupted by additive noise or interference. The method uses a “primary” input containing the corrupted Signal and a “reference” input containing noise correlated in some unknown way with the primary noise. The reference input is adaptively filtered and subtracted from the primary input to obtain the signal estimate. A desired signal corrupted by additive noise can often be recovered by an adaptive noise canceller using the least mean squares (LMS) algorithm. Computer simulations with uncorrelated Gaussian noise and signals confirm the results of the analysis and demonstrate the effectiveness of the least mean squares (LMS) algorithms.This Adaptive Noise Canceller is then useful for enhancing the S/N ratio of data collected from sensors (or sensor arrays) working in noisy environment, or dealing with potentially weak signals.
Uploaded by iserp on 04/21/2011
Digital publication details: 5 pages.

Real-Time Active Noise Cancellation with Simulinkand Data Acquisition Toolbox

issuu.com/ideseditor/docs/aceee_ijcsi_3_2_69...
This paper presents the feasibility of implementing single channel negative feedback Active Noise Cancellation technique using adaptive filters in Real-time environment[1]. In order to establish the suitability and credibility of LMS Algorithm for adaptive filtering in real world scenario, its efficiency was tested beyond system based ideal simulations. Within the MATLAB® software environment two different methods were used to perform Real-time ANC namely Simulink® and Data Acquisition ToolboxTM. Human voice is used as test signal. For processing and performing adaptive filtering, Block LMS Filter was utilised in Simulink and Error Normalised Step Size algorithm was used in between input and output of Signals by DAQ (Data Acquisition) toolbox interface.
Uploaded by ideseditor on 01/08/2013
Digital publication details: 5 pages.

Simulation of Adaptive Noise Canceller for an ECGsignal Analysis

issuu.com/ideseditor/docs/aceee_ijsip_3_1_47...
In numerous applications of signal processing, communications and biomedical we are faced with the necessity to remove noise and distortion from the signals. Adaptive filtering is one of the most important areas in digital signal processing to remove background noise and distortion. In last few years various adaptive algorithms are developed for noise cancellation. In this paper we have presented an implementation of LMS (Least Mean Square), NLMS (Normalized Least Mean Square) and RLS (Recursive Least Square) algorithms on MATLAB platform with the intention to compare their performance in noise cancellation application. We simulate the adaptive filter in MATLAB with anoisy ECG signal and analyze the performance of algorithms in terms of MSE (Mean Squared Error), SNR Improvement, computational complexity and stability.
Uploaded by ideseditor on 01/13/2013
Digital publication details: 4 pages.

Filtering Electrocardiographic Signals usingfiltered- X LMS algorithm

issuu.com/ideseditor/docs/aceee_ijsip_1_3_136...
In this paper, a simple and efficient filtered- X Least Mean Square (FXLMS) algorithm is used for the removal of different kinds of noises from the ECG signal. The adaptive filter essentially minimizes the mean-squared error between a primary input, which is the noisy ECG, and a reference input, which is either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input. Different filter structures are presented to eliminate the diverse forms of noise: baseline wander, 60 Hz power line interference, muscle artifacts and motion artifacts. Finally different adaptive structures are implemented to remove artifacts from ECG signals and tested on real signals obtained from MITBIH data base.
Uploaded by ideseditor on 01/20/2013
Digital publication details: 5 pages.

Robot

issuu.com/joseluisola/docs/robot_v...
Robot y articulacioes
Uploaded by joseluisola on 04/18/2013
Digital publication details: 321 pages.
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Development of Robust Adaptive Inversemodels using Bacterial Foraging Optimization

issuu.com/ideseditor/docs/aceee_ijcom_1_2_02...
Adaptive inverse models find applications in communication and magnetic channel equalization, recovery of digital data and adaptive linearization of sensor characteristics. In presence of outliers in the training signal, the model accuracy is severely reduced. In this paper three robust inverse models are developed by recursively minimizing robust norms using BFO based learning rule. The performance of these models is assesses through simulation study and is compared with those obtained by standard squared norm based models. It is in general, observed that the Wilcoxon norm based model provides best performance. Moreover the squared error based model is observed to perform the worst.
Uploaded by ideseditor on 01/17/2013
Digital publication details: 6 pages.

Use of Adaptive Study Material in Education in E-learning Environment

issuu.com/academic-conferences.org/docs/ejel-volume12...
Abstract: Personalised education is a topical matter today and the impact of ICT on education has been covered extensively. The adaptation of education to various types of student is an issue of a vast number of papers presented at diverse conferences. Th e topic incorporates the fields of information technologies and eLearning, but in no small part also the field of pedagogy. By interconnecting eLearning with the requirement for personalized education, we obtain a new term automatic adaptive learning. W e asked ourselves a question if the process of automatic adaptive learning (i.e. going through the electronic study course which suits student s preferences and learning style) can be modeled. The optimal adaptive process will respect students differen ces based on determined learning styles and with regard to their knowledge and skills as changed during the course. On the basis of identification of their personal characteristics and qualities, students will be presented...
Uploaded by academic-conferences.org on 07/07/2014
Digital publication details: 11 pages.

Location-Based Augmented Reality for Mobile Learning: Algorithm, System, and Implementation

issuu.com/academic-conferences.org/docs/ejel-volume13...
Abstract: AR technology can be considered as mainly consisting of two aspects: identification of real-world object and display of computer-generated digital contents related the identified real-world object. The technical challenge of mobile AR is to iden tify the real-world object that mobile device's camera aim at. In this paper, we will present a location-based object identification algorithm that has been used to identify learning objects in the 5R adaptive location-based mobile learning setting. We wi ll also provide some background of the algorithm, discuss issues in using the algorithm, and present the algorithm empowered mobile learning system and its implementation.
Uploaded by academic-conferences.org on 04/22/2015
Digital publication details: 11 pages.

Development of Robust Adaptive Inverse models usingBacterial Foraging Optimization

issuu.com/ideseditor/docs/aceee_ijcsi_2_2_44...
Adaptive inverse models find applications in communication and magnetic channel equalization, recovery of digital data and adaptive linearization of sensor characteristics. In presence of outliers in the training signal, the model accuracy is severely reduced. In this paper three robust inverse models are developed by recursively minimizing robust norms using BFO based learning rule. The performance of these models is assesses through simulation study and is compared with those obtained by standard squared norm based models. It is in general, observed that the Wilcoxon norm based model provides best performance. Moreover the squared error based model is observed to perform the worst.
Uploaded by ideseditor on 01/14/2013
Digital publication details: 6 pages.

Greek Lyric Poetry Undergraduate Course

issuu.com/academic-conferences.org/docs/ejel-volume11...
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Uploaded by academic-conferences.org on 06/10/2013
Digital publication details: 14 pages.
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