{"id":2704,"date":"2011-02-03T12:15:22","date_gmt":"2011-02-03T12:15:22","guid":{"rendered":"http:\/\/hgpu.org\/?p=2704"},"modified":"2011-02-03T12:15:22","modified_gmt":"2011-02-03T12:15:22","slug":"high-performance-power-spectrum-analysis-using-a-fpga-based-reconfigurable-computing-platform","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2704","title":{"rendered":"High Performance Power Spectrum Analysis Using a FPGA Based Reconfigurable Computing Platform"},"content":{"rendered":"<p>Power-spectrum analysis is an important tool providing critical information about a signal. The range of applications includes communication-systems to DNA-sequencing. If there is interference present on a transmitted signal, it could be due to a natural cause or superimposed forcefully. In the latter case, its early detection and analysis becomes important. In such situations having a small observation window, a quick look at power-spectrum can reveal a great deal of information, including frequency and source of interference. In this paper, we present our design of a FPGA based reconfigurable platform for high performance power-spectrum analysis. This allows for the real-time data-acquisition and processing of samples of the incoming signal in a small time frame. The processing consists of computation of power, its average and peak, over a set of input values. This platform sustains simultaneous data streams on each of the four input channels.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Power-spectrum analysis is an important tool providing critical information about a signal. The range of applications includes communication-systems to DNA-sequencing. If there is interference present on a transmitted signal, it could be due to a natural cause or superimposed forcefully. In the latter case, its early detection and analysis becomes important. In such situations having [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[3,41],"tags":[207,377,1789],"class_list":["post-2704","post","type-post","status-publish","format-standard","hentry","category-paper","category-signal-processing","tag-fft","tag-fpga","tag-signal-processing"],"views":2020,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2704","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2704"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2704\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2704"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2704"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2704"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}