Vignan University

About: Vignan University is a education organization based out in Guntur, Andhra Pradesh, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.

ASIC realization of FIR digital filters — A comparision study of power, area and delay for various architecures

Abstract: In this paper, we present the Application Specific Integrated Circuit (ASIC) implementation of Finite Impulse Response (FIR) digital filters for various architectures. The comparison was done mainly for parallel, serial and Distributed Arithmetic architectures. The performance metrics like area, delay, and power are compared. The simulation was done in Cadence TSMC 45nm Technology RTL compiler for ASIC Implementation and physical design was done using Cadence encounter.

Circulant Matrix-Based Continuous Wavelet Transform for Achieving Low Complexity Electrocardiogram Feature Extraction in Health Monitoring Applications

Abstract: In the application of remote cardiovascular monitoring, the computational complexity and power consumption need to be maintained in a considerable level in order to prevent the limitations introduced by the computationally constrained equipment’s that perform the process of continuous monitoring and analysis. In this paper, a Circulant Matrix-based Continuous Wavelet Transform (CM-CWT)-based feature extraction mechanism is contributed to minimizing the computational complexity incurred during the process of feature extraction from the input ECG signals. This proposed CM-CWT mechanism derives the advantages of the Circulant Matrix-based Continuous Wavelet Transform and Gradient-based filtering design for achieving excellent feature extraction from ECG signals with low computational complexity. The experimental investigation of the proposed CM-CWT mechanism is conducted using the factors of computational complexity, sensitivity, prediction accuracy and error rate for estimating its predominance over the compared DWT-HAAR and HIFEA approaches used for ECG feature extraction. The experiments of the proposed CM-CWT mechanism on an average is estimated to reduce the error rate to the maximum of 21% compared to the existing DWT-HAAR and HIFEA approaches used for ECG feature extraction.

An Amalgamation of Big Data Analytics with Tweet Feeds for Stock Market Trend Anticipating Systems: A Review

Abstract: In digital era, the provision of streaming data and its storage has taken wider forms where data can be in structure, semi-structured and unstructured forms. As data is increasing the storage capacity also has to be increased, and the processing of data from such huge storage may be time consuming. And it is tricky to handle and process such data via conventional software and database procedures, which lead to the research toward big data analytics. It aims at handling of massive data storage with fast processing techniques and to help companies in optimizing business, advancement of operations, making more intelligent, and fast decisions. Hence Big data analytics is an important field that derives insights from the data and prediction system is one of the famous applications of it. It takes the historical data and analyses, and then it forecasts the past and future situations basing on identified hidden patterns of data considered. The analytics can be categorized into different forms namely Business Analytics (BA) and Predictive Analytics (PA). The inclusion of skills, technologies, applications, and processes with statistical techniques adopted by organizations for their data available to impel business planning is referred to as business analytics. The forecasting approach to foresee upcoming events and trends known as Predictive Analytics, which identifies the hidden patterns and determines what is likely to happen from the historical information available using statistical and mathematical models. To enhance the forecasting process, an opinion mining can also be included. Nowadays sentiment of the people also considered to improve the accuracy level of anticipation. Effecting factors should be considered and clearly analyzed to construct accurate model so as to supply most relevant suggestions. Several researchers proposed various prediction algorithms and methods in order to construct the accuracy improved model and user satisfaction. In this chapter, authors studied various anticipating models and discussed their preference criteria. As a part of that, we studied various important preference factors in stock trend prediction and categorized them based on effecting factors. This chapter reports prospect directions in prediction models and compiling an easy guide reference list to help out the researchers.

Real-Time Self Repairable Multiplexer for Fault Tolerant Systems

Abstract: Using VLSI more number of transistors can be embedded on a single chip. As the space between transistors or circuits decreasing the system or chip is more susceptible to faults. Fault tolerant systems required to avoid inaccurate results. Multiplexer is a device which selects input signals based on select signal. The existing papers deal with only self checking multiplexer. In this paper a self repairing 2:1 multiplexer which can repair permanent and transient faults is proposed. Two different architectures are proposed for self repairing multiplexer. First architecture is having additional circuitry to repair the fault in multiplexer. In second architecture the building blocks of multiplexer like OR and AND gates itself are self repairable. These self repairing multiplexer architectures can detect and repair the single and multiple faults. The proposed architectures give 100% error recovery. The circuits are simulated using Cadence tool and verified the functionality.