Auto Encoders based Neural Networks to Predict Faultiness of VLSI Circuits
Smart Electrical Vehicle
Development of Smart Electronic System to Implement Smart Home
Multilingual Speaker Identification System through Multiple Features Analysis of Speech Signal in Multilingual Environment
Photographing a Black Hole
Development of an Intelligent Battery Charging System Based on PIC16F877A Microcontroller
Blockchain 3.0: Towards a Secure Ballotcoin Democracy through a Digitized Public Ledger in Developing Countries
Brief Introduction to Modular Multilevel Converters and Relative Concepts and Functionalities
Fetal ECG Extraction from Maternal ECG using MATLAB
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
The electrocardiogram (ECG) signal is a graphical recording of the electrical potentials generated in association with heart activity, which is one of the many important physiological signals commonly used in clinical practice. The wellbeing and status of a fetus can be accessed from a fetal ECG signal. Detecting and analysing the fetal ECG is the primary objective of electronic fetal monitoring. This paper presents a method to separate fetal ECG signals from the maternal abdomen. The method is general and is able to separate the fetal ECG signals using any number of recording electrodes, including the difficult case of single channel. This approach is based on some simple mathematical model using convolution matrix and with the help of maternal ECG, the fetal ECG signals can be extracted from the maternal abdomen. Further, the fetal ECG signals are passed through wavelets and adaptive filter to reduce the noise in the fetal ECG. The results show that the proposed method has a promising performance.
In Today's World, heart problems are the major health concern people are facing. In order to prolong life, one must be fit and should keep a check on their health. Cardiac Arrhythmia is one such heart condition, which can be diagnosed from the persons ECG (Electrocardiogram). ECG is the graphical representation of the heart's electrical activity. Any change in the waveform of the ECG depicts change in the functioning of it, which can be used as a diagnostic measure. ECG Classification is done in 3 stages, first is de-noising of the ECG signal, in the second step, the authors perform feature Extraction and finally Classifies it. The authors use FIR Filter for signal de-noising and then, they have tried to do the analysis using DOM (Difference Operation Method) for feature extraction and LDA (Linear Discriminant Analysis) for the classification of ECG signal to predict if he/she is vulnerable to any such heart condition or not. On using the above named methods the authors achieve an accuracy of 98.077% and a sensitivity of 98.009%.
This paper presents a new window for designing FIR low pass filter. While designing a FIR filter, there are two important parameters which must be taken care of which are transition width and ripples. Transition width should be as small as possible and ripples should be less both in pass band as well as stop band. There are different windows like Rectangular, Triangular, Hanning, Hamming, Blackman, etc., which are used for filter designing. The proposed window which is a modified form of Blackman window contains four cosine parameters and the simulation result shows that this window has better response when compared to Blackman Window.
This paper illustrates a new non-linear image edge-preserving filter, used for the detection and elimination of immense frequency impulse noise from digital images. Schemed method subsists of two stages i.e., pixel position detection and filtering. Simulation analysis has been performed on distinct images and results have been demonstrated in comparison to some previously designed filters. The proposed scheme works in a satisfactory way even upon noise densities in a high range of 95% to 97% in both visual presentation and quantitative measures. This designed filter preserves the edges of images with high degree of accuracy. Performance parameters such as PSNR, MAE, RMSE, and SSIM are better than most of the schemes currently in use.
Next-generation communication evolution towards 4G promises to meet the demands for ubiquitous communication. MIMO technology convolved with Optical fiber has become a mandatory requirement to achieve the goals of future communications. This paper describes the System design methodology for MIMO DSP platform. Software simulations provide flexibility, hence the authors simulate results using a software named “Optiwave's Optisystem”. The authors propose a transmission fiber for mode-division multiplexed transmission with multiple-input multiple-output (MIMO) digital signal processing supporting six spatial and polarisation modes. To increase the transmission capacity of fewmode fiber (FMF) drastically, Wavelength-Division Multiplexing Mode-Division Multiplexing (WDM-MDM), an optical MIMO technique, can be applied. With WDM-MDM, different mode groups, propagating in FMF are used to carry different information.