This paper made use of approximate entropy (ApEn) to evaluate the complexities of frequency-hopping (FH) sequences. By defining the maximal randomness of sequences with arbitrary lengths, ApEn can classify different c...This paper made use of approximate entropy (ApEn) to evaluate the complexities of frequency-hopping (FH) sequences. By defining the maximal randomness of sequences with arbitrary lengths, ApEn can classify different complex systems including stochastic processes, deterministic random process and random processes. It modified the conventional ApEn, which is used for continuous data sequence, for the discrete FH sequences. Two important theorems were given and the related main parameters were discussed. The algorithm was tested with several families of FH sequences. The simulation results show that ApEn is able to discern the changing complexities of FH sequences with a relatively small amount of samples of sequences.展开更多
基金National Natural F oundation of China(No.60 0 72 0 2 8) and High Technology Research and Developm entProgramm e of China(No.2 0 0 1AA12 3 0 14 )
文摘This paper made use of approximate entropy (ApEn) to evaluate the complexities of frequency-hopping (FH) sequences. By defining the maximal randomness of sequences with arbitrary lengths, ApEn can classify different complex systems including stochastic processes, deterministic random process and random processes. It modified the conventional ApEn, which is used for continuous data sequence, for the discrete FH sequences. Two important theorems were given and the related main parameters were discussed. The algorithm was tested with several families of FH sequences. The simulation results show that ApEn is able to discern the changing complexities of FH sequences with a relatively small amount of samples of sequences.
