SSMA is a novel neural network framework designed to overcome the quadratic complexity of Transformers by replacing dense self-attention with a combination of dynamic sparse state transitions, ...
Abstract: Linear feedback shift registers (LFSRs) over integer residue rings are widely used to generate pseudorandom number, such as ZUC algorithm, truncated LCGs, truncated MRGs. Truncated Galois ...
Abstract: The high computational cost of current state transition tensor (STT)-based high-order extended Kalman filter (HEKF) algorithms limits in-orbit orbit determination (OD) applications. This ...
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