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Full-Text Articles in Engineering
Chaotic Phase-Coded Waveforms With Space-Time Complementary Coding For Mimo Radar Applications, Sheng Hong, Fuhui Zhou, Yantao Dong, Zhixin Zhao, Yuhao Wang, Maosong Yan
Chaotic Phase-Coded Waveforms With Space-Time Complementary Coding For Mimo Radar Applications, Sheng Hong, Fuhui Zhou, Yantao Dong, Zhixin Zhao, Yuhao Wang, Maosong Yan
Electrical and Computer Engineering Faculty Publications
A framework for designing orthogonal chaotic phase-coded waveforms with space-time complementary coding (STCC) is proposed for multiple-input multiple-output (MIMO) radar applications. The phase-coded waveform set to be transmitted is generated with an arbitrary family size and an arbitrary code length by using chaotic sequences. Due to the properties of chaos, this chaotic waveform set has many advantages in performance, such as anti-interference and low probability of intercept. However, it cannot be directly exploited due to the high range sidelobes, mutual interferences, and Doppler intolerance. In order to widely implement it in practice, we optimize the chaotic phase-coded waveform set from …
A Fast Full-Search Adaptive Vector Quantizer For Video Coding, Scott E. Budge, Christian B. Peel
A Fast Full-Search Adaptive Vector Quantizer For Video Coding, Scott E. Budge, Christian B. Peel
Electrical and Computer Engineering Faculty Publications
This paper presents a novel VQ structure which provides very good quality encoding for video sequences and exploits the computational savings gained from a fast-search algorithm. It uses an adaptive-search, variable-length encoding method which allows for very fast matching of a wide range of transmission rates. Both the encoding quality and the computational benefits from the fast-search algorithm are presented. Simulations show that full-search tree residual VQ (FTRVQ) can provide up to 3 dB improvement over a similar RVQ encoder on video sequences.
Adaptive-Rate Tree-Structured Residual Vector Quantization, Christian B. Peel, X. Liu, Scott E. Budge
Adaptive-Rate Tree-Structured Residual Vector Quantization, Christian B. Peel, X. Liu, Scott E. Budge
Electrical and Computer Engineering Faculty Publications
Full-search vector quantization (VQ) provides optimal results only with high memory and computational cost. We describe the computational and memory requirements of tree-structured VQ, residual VQ (RVQ), and tree-structured RVQ. We present multiple-rate, adaptive-search implementations of these VQ structures, and simulation results with video sequences. Tree-structured RVQ provides up to 1.5 db PSNR quality improvements over RVQ, as well as significant perceptual improvement. These algorithms maintain many of the benefits of full-search VQ, while providing trade-offs between computational, storage, and performance requirements.