Pub Date : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670533
P. Velrajkumar, S. Solai Manohar, Cv Aravind, A. Darwin Jose Raju, R. Arshad
A wireless tracking and controlling the mobile robot using video capturing feature (VCF) for unmanned applications is presented. It is a wheel-based and Radio frequency (RF wireless communicated) is used for communication between controller and the robot. The available motions of the robot are forward, backward, right, left and the combination of these movements. Besides, a camera is built in the robot for tracking. The video captured by the camera is displayed in the computer or Laptop by using the Window Media Encoder (WME) software that is able to be controlled by using Windows GUI remote control. It is built for the purpose of viewing the places that humans cannot reach. Same with other robots which are built to work at dangerous environment, it can be used to explore the situation of dangerous place that human cannot reach, for example, the natural disaster area, cave, underground and so on. On the others hand, it can also serve as an investigation robot in military field. It suits the task of searching for ambush or sneaking into enemy base to gather information
提出了一种基于视频捕捉特性(VCF)的无人应用移动机器人无线跟踪控制方法。它是一种基于车轮和无线通信的射频(RF无线通信)用于控制器和机器人之间的通信。机器人的可用动作是向前、向后、向右、向左以及这些动作的组合。此外，机器人内置了一个摄像头用于跟踪。摄像机拍摄的视频通过Windows Media Encoder (WME)软件显示在计算机或笔记本电脑上，该软件可通过Windows GUI遥控器进行控制。它是为了观察人类无法到达的地方而建造的。与其他机器人一样，它是为在危险环境下工作而建造的，它可以用来探索人类无法到达的危险地方的情况，例如自然灾区，洞穴，地下等。另一方面，它也可以作为军事领域的调查机器人。它适合搜索伏击或潜入敌人基地收集情报的任务
{"title":"Development of real-time tracking and control mobile robot using video capturing feature for unmanned applications","authors":"P. Velrajkumar, S. Solai Manohar, Cv Aravind, A. Darwin Jose Raju, R. Arshad","doi":"10.1109/ICCCCT.2010.5670533","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670533","url":null,"abstract":"A wireless tracking and controlling the mobile robot using video capturing feature (VCF) for unmanned applications is presented. It is a wheel-based and Radio frequency (RF wireless communicated) is used for communication between controller and the robot. The available motions of the robot are forward, backward, right, left and the combination of these movements. Besides, a camera is built in the robot for tracking. The video captured by the camera is displayed in the computer or Laptop by using the Window Media Encoder (WME) software that is able to be controlled by using Windows GUI remote control. It is built for the purpose of viewing the places that humans cannot reach. Same with other robots which are built to work at dangerous environment, it can be used to explore the situation of dangerous place that human cannot reach, for example, the natural disaster area, cave, underground and so on. On the others hand, it can also serve as an investigation robot in military field. It suits the task of searching for ambush or sneaking into enemy base to gather information","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115596929","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 : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670731
R. Gunasundari, S. Karthikeyan
With the enormous growth on the web, users get easily lost in the rich hyper structure. Thus developing user friendly and automated tools for providing relevant information without any redundant links to the users to cater to their needs is the primary task for the website owners. But user is interested only in the informative contents and not in non-informative content blocks. Web pages often contain navigation sidebars, advertisements, search blocks, copyright notices, etc which are not content blocks. The information contained in these non-content blocks can harm web mining. So it is important to separate the informative primary content blocks from non-informative blocks. In this paper are proposed three different algorithms for removing non-content blocks from the web pages. Removal of non-informative content blocks from web pages can achieve significant storage and time saving.
{"title":"Removing non-informative blocks from the web pages","authors":"R. Gunasundari, S. Karthikeyan","doi":"10.1109/ICCCCT.2010.5670731","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670731","url":null,"abstract":"With the enormous growth on the web, users get easily lost in the rich hyper structure. Thus developing user friendly and automated tools for providing relevant information without any redundant links to the users to cater to their needs is the primary task for the website owners. But user is interested only in the informative contents and not in non-informative content blocks. Web pages often contain navigation sidebars, advertisements, search blocks, copyright notices, etc which are not content blocks. The information contained in these non-content blocks can harm web mining. So it is important to separate the informative primary content blocks from non-informative blocks. In this paper are proposed three different algorithms for removing non-content blocks from the web pages. Removal of non-informative content blocks from web pages can achieve significant storage and time saving.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117348069","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 : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670776
V. Raman, P. Sumari, J. Lekha, E. G. Dharma Prakash raj
Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. Mammography has been one of the most reliable methods for early detection of breast carcinomas. However, it is difficult for radiologists to provide both accurate and uniform evaluation for the enormous mammograms generated in widespread screening. The main objective of this paper is to enhance, detect and classify masses in digital mammogram. We develop a performance based case-based reasoning classification algorithm for mammographic findings to provide support for the clinical decision to perform biopsy of the breast. The developed classifier will be used for training and testing the images which is cancerous and noncancerous and improve the performance of the system.
{"title":"Performance based CBR Mass detection in mammograms","authors":"V. Raman, P. Sumari, J. Lekha, E. G. Dharma Prakash raj","doi":"10.1109/ICCCCT.2010.5670776","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670776","url":null,"abstract":"Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. Mammography has been one of the most reliable methods for early detection of breast carcinomas. However, it is difficult for radiologists to provide both accurate and uniform evaluation for the enormous mammograms generated in widespread screening. The main objective of this paper is to enhance, detect and classify masses in digital mammogram. We develop a performance based case-based reasoning classification algorithm for mammographic findings to provide support for the clinical decision to perform biopsy of the breast. The developed classifier will be used for training and testing the images which is cancerous and noncancerous and improve the performance of the system.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"119 48","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120826240","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 : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670785
K. Thirumalaivasan, R. Nakkeeran
This paper presents an ultra-wideband (UWB) bandpass filter for UWB applications and notch filter for the purpose of reducing interference from the WLAN (802.11a) when it coexist with UWB radio system. The bandpass filter consists of a hexagonal shaped multiple mode resonator (MMR) with interdigital coupling at both sides. The notch filter consists of four identical open ended stubs nearby the MMR which introduce a narrow rejection band in the UWB passband. Such UWB bandpass filter with notched band is useful and required in practical systems in order to avoid the interference from the existing WLAN to the UWB radio system. The analysis of the proposed filter is performed by using an electromagnetic (EM) solver, IE3D. The group delay obtained for bandpass filter is below 0.2 ns and for notch filter it is about 0.3 ns. With the above structural features the overall dimension of the filter is 38 mm (length) × 3.2 mm (breadth) × 1.6 mm (height) and the fractional bandwidth of the UWB bandpass filter is about 120.48% with return loss is about −40 dB.
{"title":"UWB bandpass filter with notched band for the rejection of 5 GHz WLAN using hexagonal multiple mode resonator","authors":"K. Thirumalaivasan, R. Nakkeeran","doi":"10.1109/ICCCCT.2010.5670785","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670785","url":null,"abstract":"This paper presents an ultra-wideband (UWB) bandpass filter for UWB applications and notch filter for the purpose of reducing interference from the WLAN (802.11a) when it coexist with UWB radio system. The bandpass filter consists of a hexagonal shaped multiple mode resonator (MMR) with interdigital coupling at both sides. The notch filter consists of four identical open ended stubs nearby the MMR which introduce a narrow rejection band in the UWB passband. Such UWB bandpass filter with notched band is useful and required in practical systems in order to avoid the interference from the existing WLAN to the UWB radio system. The analysis of the proposed filter is performed by using an electromagnetic (EM) solver, IE3D. The group delay obtained for bandpass filter is below 0.2 ns and for notch filter it is about 0.3 ns. With the above structural features the overall dimension of the filter is 38 mm (length) × 3.2 mm (breadth) × 1.6 mm (height) and the fractional bandwidth of the UWB bandpass filter is about 120.48% with return loss is about −40 dB.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125426328","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 : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670756
K. T. Shanavaz, P. Mythili
In this paper, an improved technique for evolving wavelet coefficients refined for compression and reconstruction of fingerprint images is presented. The FBI fingerprint compression standard [1, 2] uses the cdf 9/7 wavelet filter coefficients. Lifting scheme is an efficient way to represent classical wavelets with fewer filter coefficients [3, 4]. Here Genetic algorithm (GA) is used to evolve better lifting filter coefficients for cdf 9/7 wavelet to compress and reconstruct fingerprint images with better quality. Since the lifting filter coefficients are few in numbers compared to the corresponding classical wavelet filter coefficients, they are evolved at a faster rate using GA. A better reconstructed image quality in terms of Peak-Signal-to-Noise-Ratio (PSNR) is achieved with the best lifting filter coefficients evolved for a compression ratio 16∶1. These evolved coefficients perform well for other compression ratios also.
{"title":"An improved technique for evolving wavelet coefficients for fingerprint image compression","authors":"K. T. Shanavaz, P. Mythili","doi":"10.1109/ICCCCT.2010.5670756","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670756","url":null,"abstract":"In this paper, an improved technique for evolving wavelet coefficients refined for compression and reconstruction of fingerprint images is presented. The FBI fingerprint compression standard [1, 2] uses the cdf 9/7 wavelet filter coefficients. Lifting scheme is an efficient way to represent classical wavelets with fewer filter coefficients [3, 4]. Here Genetic algorithm (GA) is used to evolve better lifting filter coefficients for cdf 9/7 wavelet to compress and reconstruct fingerprint images with better quality. Since the lifting filter coefficients are few in numbers compared to the corresponding classical wavelet filter coefficients, they are evolved at a faster rate using GA. A better reconstructed image quality in terms of Peak-Signal-to-Noise-Ratio (PSNR) is achieved with the best lifting filter coefficients evolved for a compression ratio 16∶1. These evolved coefficients perform well for other compression ratios also.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126853630","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 : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670588
R. Kaur, R. Challa, Rajwinder Singh
Mobile agents are distributed programs which can move autonomously in a network, to perform tasks on behalf of user. Though mobile agents offer much more flexibility as compared to client-server computing, yet they have additional cost and issues such as security, reliability and fault tolerance which need to be addressed for successful adaptability of mobile agent technology for developing real life applications. Fault tolerance aims to provide reliable execution of agents even in face of failures that may occur on account of various errors that emerge during migration request failure, communication exceptions, system crashes or security violations. The graph based fault tolerance protocols have been successfully used for the implementation of fault tolerance in distributed computing. This paper proposes use of antecedence graphs and message logs for maintaining fault tolerance information of mobile agents. In order to reduce the overheads of the carrying fault tolerance information in form of large antecedence graphs, we propose the use of parallel checkpointing algorithm. For checkpointing, dependent agents are marked out using antecedence graphs; and only these agents are involved in process of taking checkpoints. In case of failures, the antecedence graphs and message logs are regenerated for recovery and then normal operation continued. Analysis of results show considerable improvement in terms of reduced message overhead, execution and recovery times as compared to the graph based existing approach.
{"title":"Antecedence graph based checkpointing and recovery for mobile agents","authors":"R. Kaur, R. Challa, Rajwinder Singh","doi":"10.1109/ICCCCT.2010.5670588","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670588","url":null,"abstract":"Mobile agents are distributed programs which can move autonomously in a network, to perform tasks on behalf of user. Though mobile agents offer much more flexibility as compared to client-server computing, yet they have additional cost and issues such as security, reliability and fault tolerance which need to be addressed for successful adaptability of mobile agent technology for developing real life applications. Fault tolerance aims to provide reliable execution of agents even in face of failures that may occur on account of various errors that emerge during migration request failure, communication exceptions, system crashes or security violations. The graph based fault tolerance protocols have been successfully used for the implementation of fault tolerance in distributed computing. This paper proposes use of antecedence graphs and message logs for maintaining fault tolerance information of mobile agents. In order to reduce the overheads of the carrying fault tolerance information in form of large antecedence graphs, we propose the use of parallel checkpointing algorithm. For checkpointing, dependent agents are marked out using antecedence graphs; and only these agents are involved in process of taking checkpoints. In case of failures, the antecedence graphs and message logs are regenerated for recovery and then normal operation continued. Analysis of results show considerable improvement in terms of reduced message overhead, execution and recovery times as compared to the graph based existing approach.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116047067","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 : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670778
J. Dheeba, S. Tamil Selvi
Intelligent Computer Aided Diagnosis (CAD) Systems can be used for detecting Microcalcification (MC) clusters in digital mammograms at the early stage. CAD systems help radiologists in identifying tumor patterns in an efficient and faster manner than other detection methods. In this paper, we propose a new approach for detecting tumors in mammograms using Radial Basis Function Networks (RBFNN). Prior to the detection of MC clusters features from the image are extracted and analyzed. Gabor features are extracted from the image Region of Interest (ROI) to distinguish a tumor cluster and a normal breast tissue. Once the features are extracted, they are given as input to the supervised RBFNN. The output neuron determines whether the given input ROI is cancer tissue or not. We have verified the algorithm with 322 mammograms in the Mammographic Image Analysis Society Database (MIAS). The results shows that the proposed algorithm has a sensitivity of 85.2%.
{"title":"Screening mammogram images for abnormalities using radial basis Function Neural Network","authors":"J. Dheeba, S. Tamil Selvi","doi":"10.1109/ICCCCT.2010.5670778","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670778","url":null,"abstract":"Intelligent Computer Aided Diagnosis (CAD) Systems can be used for detecting Microcalcification (MC) clusters in digital mammograms at the early stage. CAD systems help radiologists in identifying tumor patterns in an efficient and faster manner than other detection methods. In this paper, we propose a new approach for detecting tumors in mammograms using Radial Basis Function Networks (RBFNN). Prior to the detection of MC clusters features from the image are extracted and analyzed. Gabor features are extracted from the image Region of Interest (ROI) to distinguish a tumor cluster and a normal breast tissue. Once the features are extracted, they are given as input to the supervised RBFNN. The output neuron determines whether the given input ROI is cancer tissue or not. We have verified the algorithm with 322 mammograms in the Mammographic Image Analysis Society Database (MIAS). The results shows that the proposed algorithm has a sensitivity of 85.2%.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122852974","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 : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670763
S. Kurshid Jinna, L. Ganesan
This paper proposes a distortionless image data hiding algorithm based on integer wavelet transform that can hide data into the original image. The data can be retrieved and the original image can be recovered without any distortion after the hidden data are extracted. This algorithm hides data into one or more middle bit-plane( s) of the integer wavelet transform coefficients in the LH, HL and HH frequency sub bands. It can embed more data into the bit planes and also has the necessary imperceptibility requirement. The image histogram modification may be used to prevent grayscales from possible overflow or underflow. Experimental results have demonstrated the performance of the algorithm. The performance of the algorithm under different types of noise and attacks is analysed.
{"title":"Analysis of reversible image watermarking using bit plane coding and lifting wavelet transform with attacks","authors":"S. Kurshid Jinna, L. Ganesan","doi":"10.1109/ICCCCT.2010.5670763","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670763","url":null,"abstract":"This paper proposes a distortionless image data hiding algorithm based on integer wavelet transform that can hide data into the original image. The data can be retrieved and the original image can be recovered without any distortion after the hidden data are extracted. This algorithm hides data into one or more middle bit-plane( s) of the integer wavelet transform coefficients in the LH, HL and HH frequency sub bands. It can embed more data into the bit planes and also has the necessary imperceptibility requirement. The image histogram modification may be used to prevent grayscales from possible overflow or underflow. Experimental results have demonstrated the performance of the algorithm. The performance of the algorithm under different types of noise and attacks is analysed.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129422826","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 : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670758
H. Imtiaz, S. Fattah
In this paper, a frequency domain feature extraction algorithm for palm-print recognition is proposed, which efficiently exploits the local spatial variations in a palm-print image. The entire image is segmented into several narrow-width spatial bands and a palm-print recognition scheme is developed based on extracting dominant spectral features from each of these bands using two-dimensional discrete cosine transform (2D-DCT). The proposed dominant spectral feature selection algorithm offers an advantage of very low feature dimension and it is capable of capturing precisely the detail variations within the palm-print image, which results in a very high within-class compactness and between-class separability of the extracted features. From our extensive experimentations on different palm-print databases, it is found that the performance of the proposed method in terms of recognition accuracy and computational complexity is superior to that of some of the recent methods.
{"title":"A DCT-based feature extraction algorithm for palm-print recognition","authors":"H. Imtiaz, S. Fattah","doi":"10.1109/ICCCCT.2010.5670758","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670758","url":null,"abstract":"In this paper, a frequency domain feature extraction algorithm for palm-print recognition is proposed, which efficiently exploits the local spatial variations in a palm-print image. The entire image is segmented into several narrow-width spatial bands and a palm-print recognition scheme is developed based on extracting dominant spectral features from each of these bands using two-dimensional discrete cosine transform (2D-DCT). The proposed dominant spectral feature selection algorithm offers an advantage of very low feature dimension and it is capable of capturing precisely the detail variations within the palm-print image, which results in a very high within-class compactness and between-class separability of the extracted features. From our extensive experimentations on different palm-print databases, it is found that the performance of the proposed method in terms of recognition accuracy and computational complexity is superior to that of some of the recent methods.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126894516","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 : 2010-12-17DOI: 10.1109/ICCCCT.2010.5670773
D. K. Bebarta, A. K. Rout, B. Biswal, M. Biswal
A new approach to classification of non-stationary power signals based on adaptive wavelet has been considered. This paper proposes a model for non-stationary power signal disturbance classification using adaptive wavelet networks (AWN). A AWN is a combination of two sub-networks consisting of a wavelet layer and adaptive probabilistic network. The AWN has the capability of automatic adjustment of learning cycles for different classes of signals, for minimizing error. AWN models are specifically suitable for application in adaptive environments with time varying non-stationary power signals. The test results showed accurate classification, fast and adaptive learning mechanism, fast processing time and overall model effectiveness in classifying various non-stationary power signals. The classification result of the AWN (Adaptive Wavelet Network) has been compared with that of the Probabilistic Neural Network (PNN).
{"title":"Power signal classification using Adaptive Wavelet Network","authors":"D. K. Bebarta, A. K. Rout, B. Biswal, M. Biswal","doi":"10.1109/ICCCCT.2010.5670773","DOIUrl":"https://doi.org/10.1109/ICCCCT.2010.5670773","url":null,"abstract":"A new approach to classification of non-stationary power signals based on adaptive wavelet has been considered. This paper proposes a model for non-stationary power signal disturbance classification using adaptive wavelet networks (AWN). A AWN is a combination of two sub-networks consisting of a wavelet layer and adaptive probabilistic network. The AWN has the capability of automatic adjustment of learning cycles for different classes of signals, for minimizing error. AWN models are specifically suitable for application in adaptive environments with time varying non-stationary power signals. The test results showed accurate classification, fast and adaptive learning mechanism, fast processing time and overall model effectiveness in classifying various non-stationary power signals. The classification result of the AWN (Adaptive Wavelet Network) has been compared with that of the Probabilistic Neural Network (PNN).","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125637715","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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