Title :
A new cumulant based parameter estimation method for noncausal autoregressive systems
Author :
Chi, Chong-Yung ; Hwang, Jian-Lin ; Rau, Chyi-Feng
Author_Institution :
Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan
fDate :
9/1/1994 12:00:00 AM
Abstract :
Proposes a new nonlinear parameter estimation method for a noncausal autoregressive (AR) system based on a new quadratic equation relating the unknown AR parameters to higher order (⩾3) cumulants of nonGaussian output measurements in the presence of additive Gaussian noise. A gradient-type numerical optimization algorithm is used to search for the optimal AR parameter estimates. It is applicable regardless of whether or not the order of the system is known in advance; it is also applicable for the case of the causal AR system. Some simulation results are offered to justify that the proposed method is effective
Keywords :
estimation theory; identification; numerical analysis; optimisation; parameter estimation; random noise; search problems; signal processing; stochastic processes; time series; additive Gaussian noise; cumulant based parameter estimation method; gradient-type numerical optimization algorithm; higher order cumulants; nonGaussian output measurements; noncausal autoregressive systems; nonlinear parameter estimation method; quadratic equation; search; Additive noise; Array signal processing; Biomedical signal processing; Geophysical signal processing; Image processing; Parameter estimation; Signal processing; Signal processing algorithms; Speech analysis; Speech processing;
Journal_Title :
Signal Processing, IEEE Transactions on
