Pub Date : 2017-03-01DOI: 10.1109/ICSCN.2017.8085729
K. V. Gowreesrinivas, P. Samundiswary
Floating point operations like multiplication, division, addition and subtraction are important in digital signal processing applications. Out of all these, frequently used operation is multiplication and it changes the performance of single precision floating point multiplication in terms of delay and area. In this paper, performance analysis of single precision floating point multiplier is done by using Karatsuba algorithm with Vedic technique for multiplication and different Parallel Prefix adders like Sklansky, Brent-Kung and Knowles adders for exponent addition. This combination provides lesser area to compute multiplication compared to that existing multipliers. Further, the performance parameters comparison is done in terms of area and delay. The entire modules of single precision floating point multiplier are developed with Verilog HDL and synthesized with Xilinx ISE tool.
{"title":"Design and analysis of single precision floating point multiplication using Karatsuba algorithm and parallel prefix adders","authors":"K. V. Gowreesrinivas, P. Samundiswary","doi":"10.1109/ICSCN.2017.8085729","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085729","url":null,"abstract":"Floating point operations like multiplication, division, addition and subtraction are important in digital signal processing applications. Out of all these, frequently used operation is multiplication and it changes the performance of single precision floating point multiplication in terms of delay and area. In this paper, performance analysis of single precision floating point multiplier is done by using Karatsuba algorithm with Vedic technique for multiplication and different Parallel Prefix adders like Sklansky, Brent-Kung and Knowles adders for exponent addition. This combination provides lesser area to compute multiplication compared to that existing multipliers. Further, the performance parameters comparison is done in terms of area and delay. The entire modules of single precision floating point multiplier are developed with Verilog HDL and synthesized with Xilinx ISE tool.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130901869","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085418
A. Diana Andrushia, R. Thangarajan
Due to the advancement in multimedia technology, the images and videos play a major role in day today life. How the humans are looking into the image? The computational models of visual attention used in many of the computer vision tasks such as image segmentation, object recognition, image understanding, etc. The proposed method aims to construct visual saliency model with the help of the center bias and pre-attentive features. The bottom-up visual saliency model is introduced. Influence of Center bias is the key mechanism of the proposed method. Difference of Gaussian (DOG) filter and gaussian envelope function are used to identify the salient objects of an image. The experimental results of the proposed method compared with five state-of-art-methods. The benchmark database is used to obtain the performance metrics. Receiver Operating Characteristics (ROC), precision, recall and f-measure are found to analyze the performance of the proposed method.
{"title":"Center bias enhanced visual saliency detection method","authors":"A. Diana Andrushia, R. Thangarajan","doi":"10.1109/ICSCN.2017.8085418","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085418","url":null,"abstract":"Due to the advancement in multimedia technology, the images and videos play a major role in day today life. How the humans are looking into the image? The computational models of visual attention used in many of the computer vision tasks such as image segmentation, object recognition, image understanding, etc. The proposed method aims to construct visual saliency model with the help of the center bias and pre-attentive features. The bottom-up visual saliency model is introduced. Influence of Center bias is the key mechanism of the proposed method. Difference of Gaussian (DOG) filter and gaussian envelope function are used to identify the salient objects of an image. The experimental results of the proposed method compared with five state-of-art-methods. The benchmark database is used to obtain the performance metrics. Receiver Operating Characteristics (ROC), precision, recall and f-measure are found to analyze the performance of the proposed method.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121179325","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085674
N. Pazhaniraja, P. V. Paul, G. Roja, K. Shanmugapriya, B. Sonali
Bio-Inspired is a field of study that combines all the subfields together which are related to the connectionism, engineering, social behavior and emergence. Biologically inspired computing is a major subset of natural computation. The bio inspired algorithm is an effective optimization algorithm. Since the existing bio inspired algorithms can be solve the problems, an algorithm based on intelligent animals like Human, Chimpanzee and Dolphin can solve the problems in most efficient and optimized way. Dolphin is one of the most intelligent animal which can solve the complex problems in an efficient manner. This paper explains about the various swarm based optimization algorithms which helps us to analyze where these algorithms can be applied in an efficient manner. A survey on various papers is briefly explained with respect to definition, proposed model, experimental evaluation and their advantages.
{"title":"A study on recent bio-inspired optimization algorithms","authors":"N. Pazhaniraja, P. V. Paul, G. Roja, K. Shanmugapriya, B. Sonali","doi":"10.1109/ICSCN.2017.8085674","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085674","url":null,"abstract":"Bio-Inspired is a field of study that combines all the subfields together which are related to the connectionism, engineering, social behavior and emergence. Biologically inspired computing is a major subset of natural computation. The bio inspired algorithm is an effective optimization algorithm. Since the existing bio inspired algorithms can be solve the problems, an algorithm based on intelligent animals like Human, Chimpanzee and Dolphin can solve the problems in most efficient and optimized way. Dolphin is one of the most intelligent animal which can solve the complex problems in an efficient manner. This paper explains about the various swarm based optimization algorithms which helps us to analyze where these algorithms can be applied in an efficient manner. A survey on various papers is briefly explained with respect to definition, proposed model, experimental evaluation and their advantages.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123554201","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085716
P. Kasthuri, P. Prakash
Various fiber-optic dispersion effects on optical transmission system are analyzed and dispersion compensation is done using Delay Line Filter (DLF) [2]. Delay line filter is implemented using X-coupler with single source, multiple source and filter. The optical transmission system consists of transmitter, an optical DLF for compensation, fiber transmission channel and a receiver. The performance of the filter is analyzed for single mode fiber using optisystem.
分析了光纤对光传输系统的各种色散效应，并利用延迟线滤波器(Delay Line Filter, DLF)进行色散补偿[2]。延迟线滤波器采用单源、多源和滤波器的x耦合器实现。光传输系统由发射机、用于补偿的光DLF、光纤传输通道和接收机组成。利用optisystem分析了该滤波器在单模光纤中的性能。
{"title":"Performance analysis of delay line filter using X-coupler and delay line IIR filter","authors":"P. Kasthuri, P. Prakash","doi":"10.1109/ICSCN.2017.8085716","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085716","url":null,"abstract":"Various fiber-optic dispersion effects on optical transmission system are analyzed and dispersion compensation is done using Delay Line Filter (DLF) [2]. Delay line filter is implemented using X-coupler with single source, multiple source and filter. The optical transmission system consists of transmitter, an optical DLF for compensation, fiber transmission channel and a receiver. The performance of the filter is analyzed for single mode fiber using optisystem.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125110937","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085643
R. Krishnan, Prasanth Kumar Thandra, M. Baba
Steganography embeds a secret message inside an innocent looking cover medium, stealthily, without creating any attention. The cover medium used can be a text, image, audio, video, network packets, etc. To embed the secret, steganographic techniques rely on the redundant information of the used cover medium or the properties which human perceptual system fails to differentiate. Hence the choice of using text document as a cover medium is the most difficult one as they have less redundant information. However, as text documents are widely used in organizations, using text document as a cover medium might be a preferable choice in such environment. Considering this, this paper presents an overview of the existing techniques of text steganography and its classification. A comparison of the existing techniques is also provided.
{"title":"An overview of text steganography","authors":"R. Krishnan, Prasanth Kumar Thandra, M. Baba","doi":"10.1109/ICSCN.2017.8085643","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085643","url":null,"abstract":"Steganography embeds a secret message inside an innocent looking cover medium, stealthily, without creating any attention. The cover medium used can be a text, image, audio, video, network packets, etc. To embed the secret, steganographic techniques rely on the redundant information of the used cover medium or the properties which human perceptual system fails to differentiate. Hence the choice of using text document as a cover medium is the most difficult one as they have less redundant information. However, as text documents are widely used in organizations, using text document as a cover medium might be a preferable choice in such environment. Considering this, this paper presents an overview of the existing techniques of text steganography and its classification. A comparison of the existing techniques is also provided.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128694372","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085672
K. Gowrisubadra, S. Jeevitha, N. Selvarasi
The Radio Frequency Identification System (RFID) has become a widespread system and its applications have extended in most of the arenas like toll bridge, supply chain management and defense sector. The RFID technology plays a significant role in the arenas of Transport. In now a day's transportation is one of the main disputes in our country. RFID tags began to be extensively used in vehicles to automate toll processes. The spontaneous electronic toll collection system depends on RFID. In Toll Plaza collection requires an amount of actions like prohibiting the vehicle, reducing the casement, presiding the accurate coinage prior than travelers can carry on their journey. RFID technology uses tags that are fixed on the motor vehicles, through which data entrenched on the tags are read by RFID readers. The main study of this article is to explore the various existing approach while addressing the prevention of motorists and toll authorities manually perform ticket payments and also check driving without proper document, overloaded vehicle, respectively.
{"title":"A survey onrfid based automatic toll gatemanagement","authors":"K. Gowrisubadra, S. Jeevitha, N. Selvarasi","doi":"10.1109/ICSCN.2017.8085672","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085672","url":null,"abstract":"The Radio Frequency Identification System (RFID) has become a widespread system and its applications have extended in most of the arenas like toll bridge, supply chain management and defense sector. The RFID technology plays a significant role in the arenas of Transport. In now a day's transportation is one of the main disputes in our country. RFID tags began to be extensively used in vehicles to automate toll processes. The spontaneous electronic toll collection system depends on RFID. In Toll Plaza collection requires an amount of actions like prohibiting the vehicle, reducing the casement, presiding the accurate coinage prior than travelers can carry on their journey. RFID technology uses tags that are fixed on the motor vehicles, through which data entrenched on the tags are read by RFID readers. The main study of this article is to explore the various existing approach while addressing the prevention of motorists and toll authorities manually perform ticket payments and also check driving without proper document, overloaded vehicle, respectively.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121720483","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085741
N. Chaitra, P. Vijaya
Functional connectivity is the stochastic association or the dependency of two or more distinct brain regions. It is primarily used for finding patterns that are validated through statistical methods, in the context of brain connectivity. Quantification of functional connectivity is usually performed using Pearson's correlation coefficient (PCC). Many Functional magnetic resonance imaging (fMRI) studies have used PCC to quantify functional connectivity in a bivalent sense. However, the interpretation of negative fMRI responses or deactivation has proved challenging. Therefore, few have employed the absolute value of PCC (univalent) to model functional connectivity. This paper compares the two measures and assesses their performance and suitability for fMRI connectivity modeling. Connectivity analysis and classification of autistic individuals from control population is performed using these two measures. Machine learning classification is employed to quantify the predictive abilities of univalent and bivalent functional connectivity measures. This paper experimentally finds the usage of bivalent measure to be producing better classification accuracy by around 2%, which means it is more suitable for fMRI functional connectivity analysis.
{"title":"Comparing univalent and bivalent brain functional connectivity measures using machine learning","authors":"N. Chaitra, P. Vijaya","doi":"10.1109/ICSCN.2017.8085741","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085741","url":null,"abstract":"Functional connectivity is the stochastic association or the dependency of two or more distinct brain regions. It is primarily used for finding patterns that are validated through statistical methods, in the context of brain connectivity. Quantification of functional connectivity is usually performed using Pearson's correlation coefficient (PCC). Many Functional magnetic resonance imaging (fMRI) studies have used PCC to quantify functional connectivity in a bivalent sense. However, the interpretation of negative fMRI responses or deactivation has proved challenging. Therefore, few have employed the absolute value of PCC (univalent) to model functional connectivity. This paper compares the two measures and assesses their performance and suitability for fMRI connectivity modeling. Connectivity analysis and classification of autistic individuals from control population is performed using these two measures. Machine learning classification is employed to quantify the predictive abilities of univalent and bivalent functional connectivity measures. This paper experimentally finds the usage of bivalent measure to be producing better classification accuracy by around 2%, which means it is more suitable for fMRI functional connectivity analysis.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129574997","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085419
S. Sivaranjini, K. Nirmala
Breast cancer is a significantly alarming health issue for women where Dynamic Contrast Enhanced Magnetic Resonance Imaging serves as a pivot in detection, diagnoses and treatment monitoring. In this paper the response given by breast cancer patients to Neoadjuvant Chemotherapy is analyzed with Magnetic Resonance Images of these patients taken before and after treatment. The MRI images are pre-processed using Gaussian filter and the region of interest, tumor region, is identified and segmented using the adaptive k-means clustering. The features are extracted from the segmented images. The effectiveness of treatment to breast cancer is categorized according to the results obtained from the features extracted. The longest diameter measured on the maximum region proved to be prognostic factor for the physicians to decide on the other treatment measures required. Thus the experimental results show that preoperative breast tumor measurements on MRI provide us improved risk stratification methods with better surgical procedure.
{"title":"Breast cancer response post neoadjuvant chemotherapy using MRI measurements","authors":"S. Sivaranjini, K. Nirmala","doi":"10.1109/ICSCN.2017.8085419","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085419","url":null,"abstract":"Breast cancer is a significantly alarming health issue for women where Dynamic Contrast Enhanced Magnetic Resonance Imaging serves as a pivot in detection, diagnoses and treatment monitoring. In this paper the response given by breast cancer patients to Neoadjuvant Chemotherapy is analyzed with Magnetic Resonance Images of these patients taken before and after treatment. The MRI images are pre-processed using Gaussian filter and the region of interest, tumor region, is identified and segmented using the adaptive k-means clustering. The features are extracted from the segmented images. The effectiveness of treatment to breast cancer is categorized according to the results obtained from the features extracted. The longest diameter measured on the maximum region proved to be prognostic factor for the physicians to decide on the other treatment measures required. Thus the experimental results show that preoperative breast tumor measurements on MRI provide us improved risk stratification methods with better surgical procedure.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125680143","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085669
V. Lakshmanan, R. Gomathi
Aèstract-Nowadays, reconstruction of satellite images is one of the important challenges in technology. Sometimes, remote sensing images have dead pixels or pixel missing gives poor visual quality. It is mainly due to the presence of clouds, fogs, or shadows since these images are acquired by sensors at different seasons. The other serious problems in remote sensing images are instrumentation error, registration error and losses of image data during transmission. To get a good visual quality images, degraded remote sensing images are processed by using the application of inpainting. The main objectives of this image inpainting approaches are to fill lost parts of images, delete unwanted objects, remove noise in images and to enhance images quality. Image completion or image inpainting process is one in which the damaged portions are reconstructed or to fill the lost regions using data collected from surrounding areas in original image. So far, a number of inpainting algorithms are available. This paper gives a detailed survey of some inpainting methods which are suitable for remotely sensed images.
{"title":"A survey on image completion techniques in remote sensing images","authors":"V. Lakshmanan, R. Gomathi","doi":"10.1109/ICSCN.2017.8085669","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085669","url":null,"abstract":"Aèstract-Nowadays, reconstruction of satellite images is one of the important challenges in technology. Sometimes, remote sensing images have dead pixels or pixel missing gives poor visual quality. It is mainly due to the presence of clouds, fogs, or shadows since these images are acquired by sensors at different seasons. The other serious problems in remote sensing images are instrumentation error, registration error and losses of image data during transmission. To get a good visual quality images, degraded remote sensing images are processed by using the application of inpainting. The main objectives of this image inpainting approaches are to fill lost parts of images, delete unwanted objects, remove noise in images and to enhance images quality. Image completion or image inpainting process is one in which the damaged portions are reconstructed or to fill the lost regions using data collected from surrounding areas in original image. So far, a number of inpainting algorithms are available. This paper gives a detailed survey of some inpainting methods which are suitable for remotely sensed images.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117236814","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085659
R. Radhika, K. Rajashree, U. Sangeetha, S. Nandhini, R. Maheswari, D. P. Priya, B. Malarkodi, Sudhanshu Kumar
In this paper, we have intended and delineated about discerning the white space in the spectrum which is precious. The Cognitive Radio is transpiring because of its idiosyncratic nature of exploiting the unused spectrum for various praxis. Initially, we have discerned the unused frequencies in the TV band which comprises from 585 to 698 MHz and in the FM band which comprises from 87.5 MHz to 108.0 MHz in the spectrum. Subsequently, we have demonstrated the usage of this unused spectrum by transmitting an audio and a file in these bands. We have also checked the spectrum while transmitting and received the data and audio file. For implementing this we have utilized the USRP (Universal Software Radio Peripheral) and GNU Radio, a hardware and software platform respectively. The sensed spectrum and transmitted audio's screen shots are discussed in the following sections.
{"title":"Discerning white space and leveraging its potential using USRP and GNU radio","authors":"R. Radhika, K. Rajashree, U. Sangeetha, S. Nandhini, R. Maheswari, D. P. Priya, B. Malarkodi, Sudhanshu Kumar","doi":"10.1109/ICSCN.2017.8085659","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085659","url":null,"abstract":"In this paper, we have intended and delineated about discerning the white space in the spectrum which is precious. The Cognitive Radio is transpiring because of its idiosyncratic nature of exploiting the unused spectrum for various praxis. Initially, we have discerned the unused frequencies in the TV band which comprises from 585 to 698 MHz and in the FM band which comprises from 87.5 MHz to 108.0 MHz in the spectrum. Subsequently, we have demonstrated the usage of this unused spectrum by transmitting an audio and a file in these bands. We have also checked the spectrum while transmitting and received the data and audio file. For implementing this we have utilized the USRP (Universal Software Radio Peripheral) and GNU Radio, a hardware and software platform respectively. The sensed spectrum and transmitted audio's screen shots are discussed in the following sections.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130094301","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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