PowerPoint Presentation

An Introduction to Compressive SensingSpeaker: Ying-Jou ChenAdvisor: Jian-Jiun DingCompressiveCompressedSensingSamplingCSOutlineConventional Sampling & CompressionCompressive SensingWhy it is useful?FrameworkWhen and how to useRecoverySimple demo

Review

Sampling and CompressionNyquists Rate

Transform Coding6Compressive SensingCompressive Sensingwith lower rate 8Comparison

9Some ApplicationsECGOne-pixel CameraMedical Imaging: MRI

FrameworkNMNMWhen? How?Two things you must knowWhen. Signal is compressible, sparseNMNMExample ECG

HowHow to design the sampling matrix?How to decide the sampling rate (M)?MNSampling MatrixLow coherence

Low coherenceCoherenceExample: Time and Frequency

FortunatelyMore about low coherence

Random SamplingSampling RateCan be exactly recovered with high probability.

S: sparsityn: signal lengthRecoveryBUT.MNMNNMany related researchGPSR (Gradient projection for sparse reconstruction)L1-magicSparseLabBOA (Bound optimization approach)..Total ProcedurefSampling (Assume f is spare somewhere)RecoveringSum up size nx1 domain sparsesize mxn random matrix sampling (m