S.NO
SIGNAL PROCESSING
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OK9SP01 A New Construction Framework for Polyphase Complete Complementary Codes With Various Lengths OK9SP02 A Theoretical Framework of Robust H-Infinity Unscented Kalman Filter and Its Application to Power System Dynamic State Estimation OK9SP03 Advanced Low-Complexity Multicarrier Schemes Using Fast-Convolution Processing and Circular Convolution Decomposition OK9SP04 Advances in Distributed Graph Filtering
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OK9SP05 Communication-Censored ADMM for Decentralized Consensus Optimization OK9SP06 Convergence Analysis of Gaussian Belief Propagation Under High-Order Factorization and Asynchronous Scheduling OK9SP07 Correction of Corrupted Columns Through Fast Robust Hankel Matrix Completion OK9SP08 Covariance Matrix Estimation From LinearlyCorrelated Gaussian Samples OK9SP09 DeepLOB Deep Convolutional Neural Networks for Limit Order Books OK9SP10 Delta-Ramp Encoder for Amplitude Sampling and Its Interpretation as Time Encoding OK9SP11 Designing Sets of Binary Sequences for MIMO Radar Systems OK9SP12 Eigendecomposition-Free Sampling Set Selection for Graph Signals OK9SP13 Ergodicity in Stationary Graph Processes A Weak Law of Large Numbers OK9SP14 Estimation From Quantized Gaussian Measurements
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