Compressive Sensing with Optical Chaos

Area of Science:

• Optics and Photonics
• Signal Processing
• Laser Physics

Background:

• Compressive sensing (CS) enables signal reconstruction below the Nyquist-Shannon limit.
• CS offers parsimonious data storage and transmission for signals and images.
• Existing CS applications span seismology and biomedical imaging.

Purpose of the Study:

• To investigate the use of chaotic optical signals for compressive sensing.
• To construct a sensing matrix using temporal intensity chaos from external-cavity semiconductor lasers (ECSL).

Main Methods:

• Utilized optical signals generated from temporal intensity chaos.
• Employed chaotic time series with dynamics on the 100 ps timescale.
• Constructed a sensing matrix for sparse signal compression.

Main Results:

• Demonstrated the feasibility of using ECSL chaos for CS.
• Achieved compression of sparse signals using the chaotic sensing matrix.
• Identified potential for ultrahigh-speed signal compression.

Conclusions:

• Chaotic optical signals from ECSLs can effectively serve as sensing matrices in CS.
• This approach paves the way for ultrahigh-speed compressive sensing.
• The 100 ps timescale dynamics of the chaotic signals are crucial for high-speed applications.