This paper is concerned with the H∞ filtering problems for both continuous-and discrete-time Markov jumping linear systems (MJLS) with non-accessible mode information. A new design method is proposed, which greatly reduces the overdesign introduced in the derivation process. The desired filters can be obtained from the solution of convex optimization problems in terms of linear matrix inequalities (LMIs), which can be solved via efficient interior-point algorithms. Numerical examples are provided to illustrate the advantages of the proposed approach. This paper is concerned with the H∞ filtering problems for both continuous-and discrete-time Markov jumping linear systems (MJLS) ​​with non-accessible mode information. A new design method is proposed, which greatly reduces the overdesign introduced in the derivation process. The desired filters can be obtained from the solution of convex optimization problems in terms of linear matrix inequalities (LMIs), which can be solved via efficient interior-point algorithms. Numerical examples are provided to illustrate the advantages of the proposed approach.