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1、RichardBaraniukRiceUniversitydsp.rice.edu/csCompressive Sensing:ANewFrameworkforComputationalSignalProcessingPressureisonSignalProcessingNetworkedsensingplacingincreasingpressureonsignal/imageprocessinghardwareandalgstosupporthigherresolution/densersamp
2、lingADCs,cameras,imagingsystems,…+largenumbersofsensorsmulti-viewtargetdatabases,cameraarrays andnetworks,patternrecognitionsystems,+increasingnumbersofmodalitiesacoustic,seismic,RF,visual,IR,SAR,…PressureisonSignalProcessingNetworkedsensingplacingincre
3、asingpressureonsignal/imageprocessinghardwareandalgstosupporthigherresolution/densersamplingADCs,cameras,imagingsystems,…+largenumbersofsensorsmulti-viewtargetdatabases,cameraarrays andnetworks,patternrecognitionsystems,+increasingnumbersofmodalitiesaco
4、ustic,seismic,RF,visual,IR,SAR,…=delugeofdatahowtoacquire,store,fuse,processefficiently?AntipastoSensingbySamplingDataAcquisitionandRepresentationTime:A/Dconverters,receivers,…Space:cameras,imagingsystems,…Foundation:ShannonsamplingtheoremNyquistrate:mu
5、stsampleat2xhighestfrequency insignalSensingbySamplingLong-establishedparadigmfordigitaldataacquisitionsampledata(A-to-Dconverter,digitalcamera,…)compressdata(signal-dependent,nonlinear)compresstransmit/storereceivedecompresssamplesparsewavelet transfor
6、mSparsitypixelslarge wavelet coefficientswideband signal sampleslarge Gabor coefficientsManysignalscanbecompressedinsomerepresentation/basis(Fourier,wavelets,…)SensingbySamplingcompresstransmitreceivedecompresssamplesparsewavelet transformLong-establish
7、edparadigmfordigitaldataacquisitionsampledata(A-to-Dconverter,digitalcamera,…)compressdata(signal-dependent,nonlinear)brickwalltoperformanceofmodernacquisitionsystemsPastaCompressiveSensingFromSamplestoMeasurementsShannonwasapessimistworstcaseboundforan
8、ybandlimiteddataCompressivesensing(CS)principle“sparsesignalstatisticscanberecoveredfrom asmallnumberofnonadaptivelinearmeasurements”integratessensing,compression,processingbasedonnewuncertaintyprinciplesandconceptofincoherencybe
