Voice Controlled Wheelchair with Collision Avoidance
A Comparative Analysis of Neural Network Function: Resilient Back Propagation Algorithm (BPA) and Radial Basis Functions (RBF) in Multilingual Environment
Design and Implementation of Systolic Architecture Based FIR FilterDesign and Implementation of Systolic Architecture Based FIR Filter
Noise Detection and Suppression in ECG using Adaptive Filter Algorithm
Real-Time Object Detector for the Visually Impaired with Voice Feedback using OpenCV
Blockchain 3.0: Towards a Secure Ballotcoin Democracy through a Digitized Public Ledger in Developing Countries
Fetal ECG Extraction from Maternal ECG using MATLAB
Brief Introduction to Modular Multilevel Converters and Relative Concepts and Functionalities
Detection of Phase to Phase Faults and Identification of Faulty Phases in Series Capacitor Compensated Six Phase Transmission Line using the Norm of Wavelet Transform
A Novel Approach to Reduce Deafness in Classical Earphones: MUEAR
A novel mathematical ECG signal analysis approach for features extraction using LabVIEW
Filtering of ECG Signal Using Adaptive and Non Adaptive Filters
Application of Polynomial Approximation Techniques for Smoothing ECG Signals
A Novel Approach to Improve the Wind Profiler Doppler Spectra Using Wavelets
Wearable Health Monitoring Smart Gloves
This paper draws a comparative study of the induction motor stator current using Fast Fourier Transform (FFT) and Wavelet transform. The FFT is one of the most popular and oldest techniques used in signal processing to extract the frequency contents of the signal in the steady state. However, it suffers a drawback that in the process of extracting frequency information; the time information gets partially lost. This drawback is compensated by the wavelet transform. This is a new technique which is gaining popularity in many fields of science and engineering. In this paper, a single phase induction motor stator current signal data has been analyzed using FFT and Wavelet in the latest MATLAB environment. It has been shown that these two transform techniques reveals different aspects of a same stator current signal.
One of the most expensive apparatus in a power system network is the Power Transformer, which needs a continuous monitoring of its health such that the system performs efficiently. Modern power transformer is one of the most vital devices of the electric power system and its protection is critical. For this reason, the protection of power transformers has taken an important consideration by the researchers. This paper details a unique algorithm adopting wavelet packet transform method which separates the special features between magnetizing inrush and fault current, of differential current in a differential protection of a three phase transformer The performance of the proposed technique is verified under a variety of fault conditions on a typical IEEE system which is used for testing and verifying the results. Thus the proposed method is found to be fast and accurate.
In this paper, a novel approach of noise cancellation algorithm using Parallel Normalized Filtered x-LMS (P-NFxLMS) is proposed. The degraded audio signal quality can be improved by using adaptive filters. In general, Least Mean Square (LMS) adaptive filtering algorithms are used to recover corrupted signal. The implementation of LMS algorithm is simple. LMS algorithm exhibits degraded performance if the desired signal has large power fluctuations. The Normalized Fx LMS is also computationally simple and improves the performance of LMS algorithm. In this paper, an algorithm is proposed to decompose a long adaptive filter into multiple sub-filters with lower order, and are implemented in parallel to increase the convergence speed. Finally, the proposed Parallel Normalized Filtered x-LMS (P-NFxLMS) algorithm yields faster convergence with minimum Mean Square Error.
The dedicated VHF clear-air atmospheric radars built in the late 70’s and early 80’s were found to be capable of observing atmospheric parameters such as the three-dimensional wind vector. These radars measure wind continuously. Wind profiling radars yield real-time lower atmospheric wind profiles in continuous unattended operation. Wind profilers are necessary to measure the height profile of wind vector and Signal to Noise Ratio (SNR) by detecting the Doppler shift of echoes. The lower atmospheric signals, which are processed in the present work has been obtained from the LAWP radar at National Atmospheric Research Laboratory (NARL), Gadanki, India. This paper discusses estimation of the wind profile using Peak Detection Technique (PDT) and Db11 Wavelet. The fake peaks which are adjacent to the real in the radar data can be detected by applying the threshold. In order to get the true position of the object, those fake peaks should be removed and this is possible by using Peak Detection Technique. Effective Doppler shift for LAWP data is obtained by using Peak Detection Technique and compared with the doppler obtained for LAWP data using Daubechies Wavelet. Results shows that there is an effective doppler shift after using Db11 Wavelet.
In the modern digital life, the increased important roles of digital content invites new challenges for securing the exchange of digital media. This paper addresses a unique, best copyright protection and watermarking scheme for videos. In the video watermarking chrominance, channel of the selected frames is decomposed into two types of even and odd shares of video frames. For embedding, if odd share is selected, then DT-CWT (Two dimensional Dual Tree Complex Wavelet Transform) is applied on it. Video watermarking has two main process - watermark embedding and watermark extraction process. Before the watermarking embedding process, the input video sequence is converted into a number of single frames. Here the authors have applied Singular Value Decomposition and Dual Tree Complex Wavelets Transform on watermark image.
This paper aims to make understand the fundamentals and recent advancement in Multi-core Fiber Technology using Space Division Multiplexing. Few Mode Multi-core Fiber (FM-MCF) that enable Space Division Multiplexing (SDM) have greater potential to improve the transmission capacity compared to Single Spatial Mode Fiber (SSMF). The concept of Heterogeneous Few Mode Multi-core Fibers has paved its way in optical communication system by replacing Homogeneous Few Mode Multi-core Fibers which were previously opted. The uncoupled Multi-core Fibers (MCFs) which can utilize multiple cores are arranged in a fiber as spatial transmission channels and then is used for the SDM transmission. Design of 36 core and 3 mode is also demonstrated. Measurement of Inter-core XT for different bending radius is studied. And to give the readers a glimpse of recent development in Multi-core Fiber (MCF) technology, some noticeable research papers have also been discussed. System implementations based on MCF are mentioned along with future research directions.