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Optical Signal Processing For Data Compression In Ultrafast Measurement

Mididoddi, Chaitanya Kumar (2018) Optical Signal Processing For Data Compression In Ultrafast Measurement. Doctor of Philosophy (PhD) thesis, University of Kent,. (KAR id:75963)

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Abstract

Today the world is filled with continuous deluge of digital information which are ever increasing by every fraction of second. Real-time analog information such as images, RF signals needs to be sampled and quantized to represent in digital domain with help of measurement systems for information analysis, further post processing and storage. Photonics offers various advantages in terms of high bandwidth, security, immunity to electromagnetic interference, reduction in frequency dependant loss as compared to conventional electronic measurement systems. However the large bandwidth data needs to be acquired as per Nyquist principle requiring high bandwidth electronic sampler and digitizer. To address this problem, Photonic Time Stretch has been introduced to reduce the need for high speed electronic measurement equipment by significantly slowing down the speed of sampling signal. However, this generates massive data volume. Photonics-assisted methods such as Anamorphic Stretch Transform, Compressed Sensing and Fourier spectrum acquisition sensing have been addressed to achieve data compression while sampling the information. In this thesis, novel photonic implementations of each of these methods have been investigated through numerical and experimental demonstrations. The main contribution of this thesis include (1) Application of photonic implementation of compressed sensing for Optical Coherence Tomography, Fiber Bragg Grating enabled signal sensing and blind spectrum sensing applications (2) Photonic compressed sensing enabled ultra-fast imaging system (3) Fourier spectrum acquisition for RF spectrum sensing with all-optical approach (4) Adaptive non-uniform photonic time stretch methods using anamorphic stretch transform to reduce the the number of samples to be measured.

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Wang, Chao
Thesis advisor: Gomes, Nathan
Uncontrolled keywords: Compressed Sensing, Photonics, Signal Processing, Optical Coherence Tomography, Imaging
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
SWORD Depositor: System Moodle
Depositing User: System Moodle
Date Deposited: 23 Aug 2019 08:23 UTC
Last Modified: 16 Feb 2021 14:06 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/75963 (The current URI for this page, for reference purposes)
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