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 problem of echo is foremost in today’s telecommunication systems. It generally occurs in full duplex mode means when source and sink both communicate at a time. Hands-free loudspeaker telephone is a common example. It can also be seen in case of speech. In this situation the signal which is received is output through the telephone loudspeaker, the original signal is reverberated because of unwanted signal called echo. This effect in time delayed and attenuated original signal to the user. Because of this echo the signal interference caused to both user side which cause reduction in quality of signal. This interference distract to both users. Therefore, the more important task is cancellation of this echo to get signal without degradation in signal quality. This paper focus on the use of adaptive filter techniques to reduce this unwanted echo, results in increasing communication quality. A class of filters that iteratively alter its parameters is adaptive filter which is used in order to minimize a function of the difference between a desired target output and their own output. Comparison analysis of all adaptive filter algorithms is done for echo cancellation in this paper.
The aim of this project is to Design and implement an advanced Fetal Electrocardiogram (FECG) signal monitoring for both the mother and fetal analysis system using MATLAB and clean up the signal by setting some dynamic threshold. The FECG is a diagnostic tool that measures and records the electrical activity of the heart of the fetus during pregnancy. Here we use an LMS adaptive algorithm based upon FIR filter to separate fetal heart rate from maternal heart rate and to extract Fetal Electrocardiogram (FECG) from signals measured of the mother’s abdomen. The goal is to estimate the baby's heartbeat and calculate the period of the signal based on our predefined value. An adaptive noise canceller based fetal electrocardiogram extraction method is used and implemented. By using the system, could be deployed during the second trimester of pregnancy (around 20 weeks) and perhaps earlier, a woman would wear a wide belt around her abdomen fitted with several ECG electrodes. The data collected from those electrodes are then fed to a monitor and analyzed with the adaptive noise canceller algorithm, which in turn separates the different signals. We have used MATLAB because of its better performance.
Heart sounds are weak acoustic signals which provide valuable diagnostic information relating the heart valves .PCG signals are used to diagnose various pathological conditions such as heart valve disorder. Listening of heart sound via modern digital technique is becoming increasingly popular because of limitation of stethoscope being depend on physician ability of hearing experience and skill. In this paper technique to improve capability of heart sound using wavelet packet analysis is proposed for classification of normal and abnormal heart sounds. Wavelet is mathematical function that cut up data into different frequency component and thus wavelet packet method is generalization of wavelet decomposition that offers a richer range of possibilities for signal analysis.
Content Based Image Retrieval technique is becoming increasingly important in various fields in order to store, manage and Retrieve images from database based on user query. Searching is done by image features such as texture, shape or different combinations of them. Texture feature plays an important role in image processing, computer vision and Pattern recognition. In this paper we propose a novel method of using dual tree complex wavelet transform for texture feature extraction followed by feature selection and similarity matching for retrieval of leaf images which matches the query image. Thus the performance is analyzed in terms of precision and recall values. This particular proposed method may find implementation in medical field of monitoring applications.
In this paper, the combination of local binary patterns (LBP) and dual tree complex wavelet filters for content based image retrieval (CBIR). A new set of two-dimensional (2-D) rotated dual tree complex wavelet transform (DT-RCWT) are designed with dual tree complex wavelet filter coefficients, which gives improved texture retrieval performance. Most texture image retrieval systems are still incapable of providing retrieval result with high retrieval accuracy and less computational complexity. To address this problem, we propose a novel approach for texture image retrieval by using a set of dual-tree rotated complex wavelet filter (DT-RCWF) dual-tree-complex wavelet transform (DT-CWT) and local binary patterns (LBP) jointly, which obtains the texture features. LBP extracts the information based on distribution of point edges which are evaluated by taking into consideration of local difference between the center pixel and its neighbors in an image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using proposed features is found to be superior to other existing methods.
In this paper a desciption of implementation of a bilateral filter for image denoising. The bilateral filter consists of three components such as a register matrix, a photometric filter and a geometric filter. This design is a kernel based design. The input data is arranged into groups so that internal clock of the design is a multiple of the pixel clock. The bilateral filter is implemented as parallelized pipeline stucture. Kernels of different sizes can be implemented due to the modularity of the filter design and could be done with low effort. Here the bilateral filter is used for color image denoising where it reduces noise as well as preserves the details. There is only negligible quality loss.