Tensor ring decomposition (TRD) emerges a powerful technique for compactly representing high-order tensors. This approach involves decomposing a tensor into a sum of simpler rank-1 or low-rank tensors, forming a ring-like structure. TRD offers significant advantages over traditional matrix factorization methods, significantly in handling large data