Tensor ring decomposition (TRD) is a powerful technique for factorizing high-order tensors into a sum of lower-rank matrices. This decomposition can vastly reduce the memory complexity of various tensor operations. TRD has found numerous applications in diverse fields, including signal processing, where it can improve the performance of algorithms