Volume 8, Issue 11, November 2016

 

 

FPGA Hardware Resource Specific Optimal Design for FIR Filters
 

FPGA Hardware Resource Specific Optimal Design for FIR Filters

Pages: 203-207 (5) | [Full Text] PDF (298 KB)
H Ilyas, S Khan
Computer Engineering, Center for Advance Studies in Engineering, Islamabad, Pakistan

Abstract -
This paper presents a strategy to use a particular implementation that only uses a set of available resources and minimize the use of other. As an FPGA has many resources like multipliers, adders, distributed RAM, look up table and equivalent millions of gates and it completely maps application that utilizes different hardware resources. Some algorithms can be mapped to use particular resources or the other algorithms for the same application utilize other resources. In this paper FIR filters with different techniques are implemented and the resource utilization of these different algorithms are compared using Virtex 6 FPGA. The time efficient technique is also presented in this paper. At the end the tool is designed, which takes resources and coefficients from user and generates RTL verilog code according to them.
 
Index Terms - Canonic Sign Digit (CSD), Distributed Arithmetic (DA), Field-Programmable Gate Arrays (FPGA), Global Correction Vector (GCV)

Citation - H Ilyas, S Khan. "FPGA Hardware Resource Specific Optimal Design for FIR Filters." International Journal of Computer Engineering and Information Technology 8, no. 11 (2016): 203-207.

Improve the Energy Efficiency in Cognitive Radio Sensor Network using Spectrum Allocation
 

Improve the Energy Efficiency in Cognitive Radio Sensor Network using Spectrum Allocation

Pages: 208-212 (5) | [Full Text] PDF (317 KB)
A.Devi.B.E, K.Jayarajan.M.E, A.Sabari.M.Tech
Selvam College of Technology, Namakkal

Abstract -
Cooperative routing and range spectrum aggregation are two promising methods for channel sensing and switching. In this paper, we propose a Cognitive Radio Sensor Network (CRSNs) based cooperative routing protocol, termed as licensed channel, termed as cluster, for intra-cluster and inter- cluster. To the best of our insight, this is the first commitment on range accumulation based agreeable directing for CRSNs. The essential target of channel data transmission is to give higher vitality productivity, enhance throughput, and reduces system delay for Time Division Multiple Access (TDMA). A Cognitive Radio (CR) network (i.e., secondary network) opportunistically shares the radio resources with a network (i.e., Primary network). A CR-based cellular network where a cluster network shares a spectrum that belongs to an indoor system. Reducing the end-to-end delay channel is reduced. The analysis will highlight the impact of the multi-user diversity gain of both the primary and secondary users on the achievable spectral efficiency. The constraints on the reliability of sensing, the throughput and the delay of secondary User (SU) transmission. The optimal value of sensing time depends on SU waiting current channel. Found out to make the energy consumption of one data packet transmission minimized.
 
Index Terms - Cognitive radio, Sensor network, Clustering, Severity analysis, Classification

Citation - A.Devi.B.E, K.Jayarajan.M.E, A.Sabari.M.Tech. "Improve the Energy Efficiency in Cognitive Radio Sensor Network using Spectrum Allocation." International Journal of Computer Engineering and Information Technology 8, no. 11 (2016): 208-212.

Application of Text Mining for Faster Weather Forecasting
 

Application of Text Mining for Faster Weather Forecasting

Pages: 213-219 (7) | [Full Text] PDF (469 KB)
SK Jayasingh, JK Mantri, P Gahan
Biju Patnaik University of Technology
North Orissa University
Sambalpur University

Abstract -
Weather forecasting is a challenging problem in predicting the state of the climate for a future time at a given location. Weather is the state of atmosphere which is measured based on a scale of hot or cold, dry or wet, storm or calm and cloudy or clear. Human kind has tried a lot since ancient times to anticipate the future climate. It is why climate change prediction has become a very important task to the scientists and researchers of many countries. The weather is a continuous, data-intensive, multi dimensional, dynamic and chaotic process [6] and these characteristics made the weather forecasting a challenging job in the world. In order to make accurate prediction, many scientists have tried to forecast the meteorological behaviors. The objective of the research is to predict more accurately the meteorological characteristics. This article gives importance on using the fuzzy field and Natural Language Generation (NLG) that will make the weather prediction in a better and faster manner.
 
Index Terms - Weather Forecasting, J48 Decision Tree, Text Mining, Multiple Linear Regression (MLR), Root Mean Square Error (RMSE), Waikato Environment for Knowledge Analysis (WEKA), Natural Language Generation (NLG), Support Vector Machine(SVM)

Citation - SK Jayasingh, JK Mantri, P Gahan. "Application of Text Mining for Faster Weather Forecasting." International Journal of Computer Engineering and Information Technology 8, no. 11 (2016): 213-219.