This research advances hybrid soft-rigid robot simulations, achieving up to 1000 times faster computations through analytical derivatives in the GVS framework.

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%Create the coefficient matrix A. A = [1 3 -2 0 2 0; 2 6 -5 -2 4 -3; 0 0 1 5 0 3; 1 3 0 4 2 9] %Create the column matrix b of constants. %Remember, to create a column matrix, the rows are separated by ...

Abstract: Sparse Bayesian Learning (SBL) has emerged as a powerful tool for sparse signal recovery, due to its superior performance. However, the practical implementation of SBL faces a significant ...

Abstract: Matrix inversion imposes a considerable computational burden in modern communication systems. Computing-in-memory (CIM) architectures provide a promising solution by minimizing data movement ...