Pub Date : 2017-12-01DOI: 10.1109/ICCS1.2017.8325977
Jiya A. Sam, Aswathy K. Nair
The FFT processor is an essential part utilized for implementing the frameworks of OFDM. Due to its computational necessities, it involves large area and devours high power if implemented in hardware. In this paper, a low power and area efficient pipelined FFT processor using higher radix architecture and folding transformation is presented. The implemented low power FFT has a simple structure as that of radix 2 while utilizing the advantages of higher radix architecture. Higher radix algorithm minimizes the number of multiplication with twiddle factor which in turn reduces the large power utilization in FFT. Radix 22 multipath feedforward architecture is proposed in this paper. As various sequence are computed parallel, a high throughput can be achieved. Hardware resources needed for the presented architecture is much less than the multipath feedback architecture. Reduced chip area and lower power consumption are the merits of this FFT processor. Verilog coding for designed architecture is simulated and synthesized in Xilinx ISE Design Suite 12.1.
{"title":"Fast computation of FFT in OFDM system","authors":"Jiya A. Sam, Aswathy K. Nair","doi":"10.1109/ICCS1.2017.8325977","DOIUrl":"https://doi.org/10.1109/ICCS1.2017.8325977","url":null,"abstract":"The FFT processor is an essential part utilized for implementing the frameworks of OFDM. Due to its computational necessities, it involves large area and devours high power if implemented in hardware. In this paper, a low power and area efficient pipelined FFT processor using higher radix architecture and folding transformation is presented. The implemented low power FFT has a simple structure as that of radix 2 while utilizing the advantages of higher radix architecture. Higher radix algorithm minimizes the number of multiplication with twiddle factor which in turn reduces the large power utilization in FFT. Radix 22 multipath feedforward architecture is proposed in this paper. As various sequence are computed parallel, a high throughput can be achieved. Hardware resources needed for the presented architecture is much less than the multipath feedback architecture. Reduced chip area and lower power consumption are the merits of this FFT processor. Verilog coding for designed architecture is simulated and synthesized in Xilinx ISE Design Suite 12.1.","PeriodicalId":367360,"journal":{"name":"2017 IEEE International Conference on Circuits and Systems (ICCS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115092603","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 : 2017-11-07DOI: 10.1109/iccs1.2017.8326028
B. Anoop, S. Sankar
Morphology of fundus image indicates diseases like diabetic retinopathy and glaucoma. Features of the retinal images allow ophthalmologist to perform retinal disease identification. Presence of lesions in the fundus retinal image is initial sign of diabetic retinopathy. The paper proposes a method for the detection of lesions in retinopathy fundus images based on segmented structure of retina. Morphological operators extract image features and selected features are passed into the support vector machine (SVM) classifier which classifies the images into normal and abnormal classes.
{"title":"Lesion detection using segmented structure of retina","authors":"B. Anoop, S. Sankar","doi":"10.1109/iccs1.2017.8326028","DOIUrl":"https://doi.org/10.1109/iccs1.2017.8326028","url":null,"abstract":"Morphology of fundus image indicates diseases like diabetic retinopathy and glaucoma. Features of the retinal images allow ophthalmologist to perform retinal disease identification. Presence of lesions in the fundus retinal image is initial sign of diabetic retinopathy. The paper proposes a method for the detection of lesions in retinopathy fundus images based on segmented structure of retina. Morphological operators extract image features and selected features are passed into the support vector machine (SVM) classifier which classifies the images into normal and abnormal classes.","PeriodicalId":367360,"journal":{"name":"2017 IEEE International Conference on Circuits and Systems (ICCS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134038913","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：