The measurement matrix construction algorithm is one of important research direction in compressed sensing. A measurement matrix algorithm based on Logistic Chaos-Bernoulli sequence is proposed according to the pseudo-random property of chaos sequence. It uses the one-dimensional Logistic chaotic system to generate the chaotic sequence, the pseudo-random sequence with Bernoulli distribution is generated by the symbol function and the sequence is used to construct the measurement matrix. Simulation results show that, the proposed algorithm performs better than the Bernoulli random measurement matrix and the PSNR of construct signal is improved about 1~3 dB, and it is feasible and effective by numerical analysis after comparing with other types of measure matrix.

The Logistic Chaos-Bernoulli sequence-based measurement matrix algorithm improves PSNR by 1-3 dB in compressed sensing compared to Bernoulli random measurement matrix.

Measurement matrix construction algorithm for compressed sensing based on chaos sequence

Key Takeaway: The Logistic Chaos-Bernoulli sequence-based measurement matrix algorithm improves PSNR by 1-3 dB in compressed sensing compared to Bernoulli random measurement matrix.