This work describes a novel adaptive matrix/vector gradient (AMVG) algorithm for design of IIR filters and ARMA signal models. The AMVG algorithm can track to IIR filters and ARMA systems having poles also outside the...This work describes a novel adaptive matrix/vector gradient (AMVG) algorithm for design of IIR filters and ARMA signal models. The AMVG algorithm can track to IIR filters and ARMA systems having poles also outside the unit circle. The time reversed filtering procedure was used to treat the unstable conditions. The SVD-based null space solution was used for the initialization of the AMVG algorithm. We demonstrate the feasibility of the method by designing a digital phase shifter, which adapts to complex frequency carriers in the presence of noise. We implement the half-sample delay filter and describe the envelope detector based on the Hilbert transform filter.展开更多
The problem of approximate joint diagonalization of a set of matrices is instrumental in numerous statistical signal processing applications. This paper describes a relative gradient non-orthogonal approximate joint d...The problem of approximate joint diagonalization of a set of matrices is instrumental in numerous statistical signal processing applications. This paper describes a relative gradient non-orthogonal approximate joint diagonalization （AJD） algorithm based on a non-least squares AJD criterion and a special AJD using a non-square diagonalizing matrix and an AJD method for ill-conditioned matrices. Simulation results demonstrate the better performance of the relative gradient AJD algorithm compared with the conventional least squares （LS） criteria based gradient-type AJD algorithms. The algorithm is attractive for practical applications since it is simple and efficient.展开更多
文摘This work describes a novel adaptive matrix/vector gradient (AMVG) algorithm for design of IIR filters and ARMA signal models. The AMVG algorithm can track to IIR filters and ARMA systems having poles also outside the unit circle. The time reversed filtering procedure was used to treat the unstable conditions. The SVD-based null space solution was used for the initialization of the AMVG algorithm. We demonstrate the feasibility of the method by designing a digital phase shifter, which adapts to complex frequency carriers in the presence of noise. We implement the half-sample delay filter and describe the envelope detector based on the Hilbert transform filter.
基金Supported by the Basic Research Foundation of Tsinghua National Laboratory for Information Science and Technology (TNList) the National Natural Science Foundation of China (No. 60675002)
文摘The problem of approximate joint diagonalization of a set of matrices is instrumental in numerous statistical signal processing applications. This paper describes a relative gradient non-orthogonal approximate joint diagonalization （AJD） algorithm based on a non-least squares AJD criterion and a special AJD using a non-square diagonalizing matrix and an AJD method for ill-conditioned matrices. Simulation results demonstrate the better performance of the relative gradient AJD algorithm compared with the conventional least squares （LS） criteria based gradient-type AJD algorithms. The algorithm is attractive for practical applications since it is simple and efficient.
