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
Diagnosis of diseases using ECG signal required, classification of beat, which is the main criteria for arrhythmia detection. But accuracy of the detected beat plays an important role in the diagnosis of the disease using ECG signal. This paper describes an evaluation method which is used to analyze the ECG signal and help in diagnosis of cardiac arrhythmia diseases. The evaluation method is used in classification of the beats of ECG signal. Generally there are two types of beats present in human heartbeat – normal beats (NORM) and abnormal beats (LBBB, RBBB, APC, and VPC). For diagnosis, these parameters are first determined. These values can be classified with the help of any existing methodology. This paper aims to check the accuracy of the beat (normal and abnormal beat). Statistical parameters are used for calculating accuracy. Statistical parameters are nothing but the parameter which is used to check the accuracy of the detected beat. The proposed method in this paper evaluates statistical parameters namely Sensitivity (Se), Specificity (Sp), Positive Predictive Values (PPV,) and Negative Predictive Values (NPV) and compares it with the ideal values. The proposed method can be used to detect the accuracy of any existing heartbeat classification methods.
Lung cancer is the most challenging problem chasing the scientific and medical fields in several countries around the world. Several medical modalities are specialised to diagnosis the extinct of disease via PET, MRI, CT, US and DICOM. Automated Computer Aided Diagnosing (CAD) system has shown its improvements in the detection of lung cancer using advanced radiology. CAD system merges geometric and intensity models to improve particular area of anatomical structure. Nodules are comparatively smaller than 3-4 cm in diameter and are common abnormalities that are adjacent to vessels or chest wall. Detection of non-spherical shaped nodules is a primary difficulty. Sixty percent of all nodules are not harmful but malignant nodules may be lung cancer tumours. To identify these nodules the methods like intensity thresholding or model based might fail. In this paper the nodules are extracted from the DICOM lung image in the noisy environment such as Gaussian, salt and pepper, Poisson and speckle using morphology and watershed algorithm. The nodules are extracted from the lung portion using different edge detection operators such as Gaussian, Laplacian, prewitt, LOG, Unsharp, average and Sobel in presence of noise and various sizes of the structuring element. These results support to examine and calculate the influence of noises on the DICOM images in extracting the nodules.
This paper describes a high-speed and low-complexity implementation of FIR filter using least mean square technique. The proposed structure of multiplexed based zero-adaptation-delay structure and two adaptation delay structure for a direct LMS adaptive FIR filter. This paper describes the proposed adder technique provides much faster convergence and lower complexity for obtaining lower area, power dissipation, high speed and lower propagation delay. The multiplexer circuits were schematized using the DSCH2 schematic design tool, and their layouts were generated with the Micro wind 2 VLSI layout CAD tool. The parameter analyses were performed with a BSIM4 analyzer. The proposed multiplex -based filters are use carry save adder as well as other existing adder circuit in terms of power dissipation, propagation delay, latency, and throughput. Our proposed structure involves the minimum power. Finally the simulations are done using Xilinx ISE design suite to get power and implemented on Spartan 3E FPGA kit.
In recent years, Digitally Controlled Delay-Lines (DCDL) is a key block in number of applications and play the role of DAC in traditional circuits. This paper presents a totally glitch free DCDL which overcame the limitation of a NAND based DCDL using strobe control method. Using this logic a clock is presented, that reduces the output jitter when compared to the existing method. The existing method uses a delay control code and reduces the delay of about 40%, but it consumes more power and less area efficient. By using strobe controlled logic, the peak to peak absolute output jitter of 70-80% were reduced. As an example application, All-digital spread-spectrum clock generator (SSCG), All-digital phase-locked loops (ADPLL), Phase-locked loop (PLL) were used.
This paper presents a comprehensive analysis of spectrum sensing (SS) in cognitive radio (CR) network. The main function of cognitive radio is detecting unused spectrum and sharing it without harmful interference to the licensed user. Cooperative spectrum sensing refers to incorporation of multiple secondary users (SU) to analyze the primary user (PU) signal in order to achieve more accurate detection performance. In order to solve the sensing failure problem in conventional two threshold energy detection method soften hard decision fusion mechanism is used exploiting all the sensing results. Consideration of the confused region which is the intersection of the energy distribution of PU signal and noise. SUs could not distinguish between the absence or presence of the primary user in the confused region. So the fusion center makes a soft combination of the observations. The objective of this paper is to produce an efficient spectrum sensing algorithms using two thresholds with soften hard decision fusion mechanism.
When the errors introduced by the information channel are unacceptable then the channel coding is needed. The use of channel coders with source coders provides the efficient and reliable transmission in the presence of noise. The use of channel coders with source coders provides the efficient and reliable transmission in the presence of noise. Coding permits an increased rate of information transfer at a fixed error rate, or a reduced error rate for a fixed transfer rate. A convolution coder accepts a fixed number of message symbols and produces a fixed number of code symbols, but its computations depends not only on the current set of input symbols but also on some of previous input symbols. Through this paper we have illustrated design of convolution encoder using time domain approach with VHDL platform. The target technology is used as Sparten FPGA device.