Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208280
J. Beevi, N. Deivasigamani
A Knowledge Base is a special kind of data base used for storage and retrieval of knowledge. From the perspective of knowledge creators, maintenance and creation of knowledge base is a crucial activity in the life cycle of knowledge management. This paper presents a novel approach to the creation of knowledge base. The main focus of our approach is to extract the knowledge from unstructured web documents and create a knowledge base. Preprocessing techniques such as tokenizing, stemming are performed on the unstructured input web documents. Meanwhile, Similarity and redundancy computation is performed for duplicate knowledge removal. The extracted knowledge is organized and converted to XML documents. XCLS clustering is made on XML documents. Finally, Knowledge base is designed for storing extracted XML documents. A query interface has been developed to retrieve the search knowledge. To test the usefulness and ease of use of our prototype, we used the Technology Acceptance Model (TAM) to evaluate the system. Results are promising.
{"title":"A new approach to the design of knowledge base using XCLS clustering","authors":"J. Beevi, N. Deivasigamani","doi":"10.1109/ICPRIME.2012.6208280","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208280","url":null,"abstract":"A Knowledge Base is a special kind of data base used for storage and retrieval of knowledge. From the perspective of knowledge creators, maintenance and creation of knowledge base is a crucial activity in the life cycle of knowledge management. This paper presents a novel approach to the creation of knowledge base. The main focus of our approach is to extract the knowledge from unstructured web documents and create a knowledge base. Preprocessing techniques such as tokenizing, stemming are performed on the unstructured input web documents. Meanwhile, Similarity and redundancy computation is performed for duplicate knowledge removal. The extracted knowledge is organized and converted to XML documents. XCLS clustering is made on XML documents. Finally, Knowledge base is designed for storing extracted XML documents. A query interface has been developed to retrieve the search knowledge. To test the usefulness and ease of use of our prototype, we used the Technology Acceptance Model (TAM) to evaluate the system. Results are promising.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124868487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208285
D. A. Kumar, T. Ummal, Sariba Begum
Electronic Voting Machine (EVM) is a simple electronic device used to record votes in place of ballot papers and boxes which were used earlier in conventional voting system. Fundamental right to vote or simply voting in elections forms the basis of democracy. All earlier elections be it state elections or centre elections a voter used to cast his/her favorite candidate by putting the stamp against his/her name and then folding the ballot paper as per a prescribed method before putting it in the Ballot Box. This is a long, time-consuming process and very much prone to errors. This situation continued till election scene was completely changed by electronic voting machine. No more ballot paper, ballot boxes, stamping, etc. all this condensed into a simple box called ballot unit of the electronic voting machine. Because biometric identifiers cannot be easily misplaced, forged, or shared, they are considered more reliable for person recognition than traditional token or knowledge based methods. So the Electronic voting system has to be improved based on the current technologies viz., biometric system. This article discusses complete review about voting devices, Issues and comparison among the voting methods and biometric EVM.
{"title":"Electronic voting machine — A review","authors":"D. A. Kumar, T. Ummal, Sariba Begum","doi":"10.1109/ICPRIME.2012.6208285","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208285","url":null,"abstract":"Electronic Voting Machine (EVM) is a simple electronic device used to record votes in place of ballot papers and boxes which were used earlier in conventional voting system. Fundamental right to vote or simply voting in elections forms the basis of democracy. All earlier elections be it state elections or centre elections a voter used to cast his/her favorite candidate by putting the stamp against his/her name and then folding the ballot paper as per a prescribed method before putting it in the Ballot Box. This is a long, time-consuming process and very much prone to errors. This situation continued till election scene was completely changed by electronic voting machine. No more ballot paper, ballot boxes, stamping, etc. all this condensed into a simple box called ballot unit of the electronic voting machine. Because biometric identifiers cannot be easily misplaced, forged, or shared, they are considered more reliable for person recognition than traditional token or knowledge based methods. So the Electronic voting system has to be improved based on the current technologies viz., biometric system. This article discusses complete review about voting devices, Issues and comparison among the voting methods and biometric EVM.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132838731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208284
S. P. Algur, N. T. Pendari
Web spamming refers to actions intended to mislead search engines and give some pages higher ranking than they deserve. Fundamentally, Web spam is designed to pollute search engines and corrupt the user experience by driving traffic to particular spammed Web pages, regardless of the merits of those pages. Recently, there is dramatic increase in amount of web spam, leading to a degradation of search results. Most of the existing web spam detection methods are supervised that require a large set of training web pages. The proposed system studies the problem of unsupervised web spam detection. It introduces the notion of spamicity to measure how likely a page is spam. Spamicity is a more flexible measure than the traditional supervised classification methods. In the proposed system link and content spam techniques are used to determine the spamicity score of web page. A threshold is set by empirical analysis which classifies the web page into spam or non spam.
{"title":"Hybrid spamicity score approach to web spam detection","authors":"S. P. Algur, N. T. Pendari","doi":"10.1109/ICPRIME.2012.6208284","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208284","url":null,"abstract":"Web spamming refers to actions intended to mislead search engines and give some pages higher ranking than they deserve. Fundamentally, Web spam is designed to pollute search engines and corrupt the user experience by driving traffic to particular spammed Web pages, regardless of the merits of those pages. Recently, there is dramatic increase in amount of web spam, leading to a degradation of search results. Most of the existing web spam detection methods are supervised that require a large set of training web pages. The proposed system studies the problem of unsupervised web spam detection. It introduces the notion of spamicity to measure how likely a page is spam. Spamicity is a more flexible measure than the traditional supervised classification methods. In the proposed system link and content spam techniques are used to determine the spamicity score of web page. A threshold is set by empirical analysis which classifies the web page into spam or non spam.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124271359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208361
J. Saranya, S. Malarkhodi
Image segmentation is important tasks in medical image analysis. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The segmentation of an ultrasound image is a difficult task as it suffers from speckle noise. The main aim of this work is to segment the fibroid in the uterus. Uterine fibroid is the most common benign tumour of the female in the world. Uterine Fibroid segmentation in patient is the challenging task manually. Exactly extracting the fibroid in the uterus is the challenging task because of size, location and low contrast boundaries. Instead of doing the segmentation manually, this work proposes a new method for segmenting the fibroid in the uterus. The performance of this method is also commendable.
{"title":"Filtering and segmentation of a uterine fibroid with an ultrasound images","authors":"J. Saranya, S. Malarkhodi","doi":"10.1109/ICPRIME.2012.6208361","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208361","url":null,"abstract":"Image segmentation is important tasks in medical image analysis. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The segmentation of an ultrasound image is a difficult task as it suffers from speckle noise. The main aim of this work is to segment the fibroid in the uterus. Uterine fibroid is the most common benign tumour of the female in the world. Uterine Fibroid segmentation in patient is the challenging task manually. Exactly extracting the fibroid in the uterus is the challenging task because of size, location and low contrast boundaries. Instead of doing the segmentation manually, this work proposes a new method for segmenting the fibroid in the uterus. The performance of this method is also commendable.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115033657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208347
Gokulnath Thandavarayan, K. Sangeetha, S. Seerangan
Mobile Ad Hoc Network (MANET) is a wireless communication with a collection of devices that communicate with each other without the aid of any centralized administrator. Due to its properties MANET environment is prone to attacks in routes. ORZEF is a self-motivated routing system to provide has less security secure routing. When a node enters into a zone it distributes its secret key upto two hop count nodes and it shares their secret keys by using asymmetric key encryption. For each node routing zone is defined separately using its radius. When there is a malicious activity in the environment the authentication algorithm is initiated to isolate the malicious nodes. As a result of this scheme, the network will be able to effectively isolate the malicious nodes. Through extensive simulation analysis using QualNet simulator it is concluded that this scheme provides an efficient approach towards security and easier detection of the malicious nodes in the mobile ad hoc network and the power also utilized effectively.
{"title":"ORZEF: An optimized routing using zone to establish security in MANET using multipath and friend-based ad hoc routing","authors":"Gokulnath Thandavarayan, K. Sangeetha, S. Seerangan","doi":"10.1109/ICPRIME.2012.6208347","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208347","url":null,"abstract":"Mobile Ad Hoc Network (MANET) is a wireless communication with a collection of devices that communicate with each other without the aid of any centralized administrator. Due to its properties MANET environment is prone to attacks in routes. ORZEF is a self-motivated routing system to provide has less security secure routing. When a node enters into a zone it distributes its secret key upto two hop count nodes and it shares their secret keys by using asymmetric key encryption. For each node routing zone is defined separately using its radius. When there is a malicious activity in the environment the authentication algorithm is initiated to isolate the malicious nodes. As a result of this scheme, the network will be able to effectively isolate the malicious nodes. Through extensive simulation analysis using QualNet simulator it is concluded that this scheme provides an efficient approach towards security and easier detection of the malicious nodes in the mobile ad hoc network and the power also utilized effectively.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134600988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208377
S. Vivek, J. Aravinth, S. Valarmathy
Biometrics consists of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. This paper describes the feature extraction techniques for three modalities viz. fingerprint, iris and face. The extracted information from each modality is stored as a template. The information are fused at the match score level using a density based score level fusion, GMM followed by the Likelihood ratio test. GMM parameters are estimated from training data using the iterative Expectation-Maximization (EM) algorithm.
{"title":"Feature extraction for multimodal biometric and study of fusion using Gaussian mixture model","authors":"S. Vivek, J. Aravinth, S. Valarmathy","doi":"10.1109/ICPRIME.2012.6208377","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208377","url":null,"abstract":"Biometrics consists of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. This paper describes the feature extraction techniques for three modalities viz. fingerprint, iris and face. The extracted information from each modality is stored as a template. The information are fused at the match score level using a density based score level fusion, GMM followed by the Likelihood ratio test. GMM parameters are estimated from training data using the iterative Expectation-Maximization (EM) algorithm.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"22 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130668397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208375
I. Julie, E. Kirubakaran
The most important application of Microarray for gene expression analysis is used to discover or classify the unknown tissue samples with the help of known tissue samples. Several Data Mining Classifiers have been proposed recently to predict/identify the cancer patterns. In this research work, we have focused and studied a few Classification Techniques such as Support Vector Machine (SVM), Nearest Neighbor Classifier (k-NN), ICS4, Non-Parallel Plane Proximal Classifier (NPPC), NPPC-SVM, and Margin-based Feature Elimination-SVM (MFE-SVM). The performances of these classifiers have been analyzed in terms of Threshold Level, Execution Time, Memory Usage and Memory Utilization. From our experimental results, we revealed that the Threshold level and Execution Time to predict the Cancer Patterns are different for different Classifiers. Our experimental results established that among the above identified classifiers, the k-NN classifier achieves less Threshold to predict the cancer pattern, but however it consumes more execution time, whereas the MFE-SVM achieves less execution time to predict the cancer pattern, but it still needs more threshold to predict the Pattern. That is to find the best single classifier in terms of Threshold and Execution Time is still complicated. To address this major issue, we have proposed an efficient Classifier called Maximizing Feature Elimination Technique based Hybrid Classifier (MFE-HC), which is the combination of both k-NN and SVM classifiers. From the results, it is established that our proposed work performs better than both the k-NN and MFE-SVM Classifiers interms of Threshold and Execution Time.
{"title":"MFE-HC: The maximizing feature elimination technique based hybrid classifier for cancer molecular pattern discovery","authors":"I. Julie, E. Kirubakaran","doi":"10.1109/ICPRIME.2012.6208375","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208375","url":null,"abstract":"The most important application of Microarray for gene expression analysis is used to discover or classify the unknown tissue samples with the help of known tissue samples. Several Data Mining Classifiers have been proposed recently to predict/identify the cancer patterns. In this research work, we have focused and studied a few Classification Techniques such as Support Vector Machine (SVM), Nearest Neighbor Classifier (k-NN), ICS4, Non-Parallel Plane Proximal Classifier (NPPC), NPPC-SVM, and Margin-based Feature Elimination-SVM (MFE-SVM). The performances of these classifiers have been analyzed in terms of Threshold Level, Execution Time, Memory Usage and Memory Utilization. From our experimental results, we revealed that the Threshold level and Execution Time to predict the Cancer Patterns are different for different Classifiers. Our experimental results established that among the above identified classifiers, the k-NN classifier achieves less Threshold to predict the cancer pattern, but however it consumes more execution time, whereas the MFE-SVM achieves less execution time to predict the cancer pattern, but it still needs more threshold to predict the Pattern. That is to find the best single classifier in terms of Threshold and Execution Time is still complicated. To address this major issue, we have proposed an efficient Classifier called Maximizing Feature Elimination Technique based Hybrid Classifier (MFE-HC), which is the combination of both k-NN and SVM classifiers. From the results, it is established that our proposed work performs better than both the k-NN and MFE-SVM Classifiers interms of Threshold and Execution Time.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130594397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208303
Sagadevan K V Babu, Samson S Arivumani, Asst Pg Scholar, Asst Prof, Prof
Reconfigurability and low complexity are two key requirements of Finite Impulse Response (FIR) filters employed in multi-standard wireless communication systems. In this paper, two new reconfigurable architectures of low complexity FIR filters are proposed, namely Constant Shift Method and Programmable Shift Method. The proposed FIR filter architecture is capable of operating for different wordlength filter coefficients without any overhead in the hardware circuitry. This reconfigurable architecture filters can be efficiently implemented by using common subexpression elimination (CSE) algorithm. Design examples show that the proposed 3 bit Binary Common Subexpression Elimination Constant Shift Method architecture offer speed improvement and Programmable Shift Method architecture offer area and power reduction compared to existing reconfigurable FIR filter.
{"title":"Novel reconfigurable architecture with low complexity FIR filter","authors":"Sagadevan K V Babu, Samson S Arivumani, Asst Pg Scholar, Asst Prof, Prof","doi":"10.1109/ICPRIME.2012.6208303","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208303","url":null,"abstract":"Reconfigurability and low complexity are two key requirements of Finite Impulse Response (FIR) filters employed in multi-standard wireless communication systems. In this paper, two new reconfigurable architectures of low complexity FIR filters are proposed, namely Constant Shift Method and Programmable Shift Method. The proposed FIR filter architecture is capable of operating for different wordlength filter coefficients without any overhead in the hardware circuitry. This reconfigurable architecture filters can be efficiently implemented by using common subexpression elimination (CSE) algorithm. Design examples show that the proposed 3 bit Binary Common Subexpression Elimination Constant Shift Method architecture offer speed improvement and Programmable Shift Method architecture offer area and power reduction compared to existing reconfigurable FIR filter.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116717916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208294
G. M. Nasira, N. Hemageetha
Each and every sector in this digital world is undergoing a dramatic change due to the influence of IT field. The agricultural sector needs more support for its development in developing countries like India. Price prediction helps the farmers and also Government to make effective decision. Based on the complexity of vegetable price prediction, making use of the characteristics of neural networks such as self-adapt, self-study and high fault tolerance, to build up the model of Back-propagation neural network to predict vegetable price. A prediction model was set up by applying the neural network. Taking tomato as an example, the parameters of the model are analyzed through experiment. At the end of the result of Back-propagation neural network shows absolute error percentage of monthly and weekly vegetable price prediction and analyze the accuracy percentage of the price prediction.
{"title":"Vegetable price prediction using data mining classification technique","authors":"G. M. Nasira, N. Hemageetha","doi":"10.1109/ICPRIME.2012.6208294","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208294","url":null,"abstract":"Each and every sector in this digital world is undergoing a dramatic change due to the influence of IT field. The agricultural sector needs more support for its development in developing countries like India. Price prediction helps the farmers and also Government to make effective decision. Based on the complexity of vegetable price prediction, making use of the characteristics of neural networks such as self-adapt, self-study and high fault tolerance, to build up the model of Back-propagation neural network to predict vegetable price. A prediction model was set up by applying the neural network. Taking tomato as an example, the parameters of the model are analyzed through experiment. At the end of the result of Back-propagation neural network shows absolute error percentage of monthly and weekly vegetable price prediction and analyze the accuracy percentage of the price prediction.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128087383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208373
S. Sekar, K. Prabakaran, E. Paramanathen
In this paper, a new technique known as Single Term Haar Wavelet Series (STHWS) has been presented to determine the solutions for the time varying linear and non-linear singular systems. The exact solutions and the solutions by the classical fourth order Runge-Kutta (RK) method for the problems of time varying linear and non-linear singular systems are compared with the simulated results by STHWS method. This new approach provides a better accuracy in finding discrete solutions of time varying systems for any length of time and it can be easily implemented in a digital computer which is an added advantage of this method.
{"title":"Single-term Haar wavelet series technique for time varying linear and non-linear singular systems","authors":"S. Sekar, K. Prabakaran, E. Paramanathen","doi":"10.1109/ICPRIME.2012.6208373","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208373","url":null,"abstract":"In this paper, a new technique known as Single Term Haar Wavelet Series (STHWS) has been presented to determine the solutions for the time varying linear and non-linear singular systems. The exact solutions and the solutions by the classical fourth order Runge-Kutta (RK) method for the problems of time varying linear and non-linear singular systems are compared with the simulated results by STHWS method. This new approach provides a better accuracy in finding discrete solutions of time varying systems for any length of time and it can be easily implemented in a digital computer which is an added advantage of this method.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127752329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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