Statistical Methods in Control & Signal Processing

Presenting statistical and stochastic methods for the analysis and design of technological systems in engineering and applied areas, this work documents developments in statistical modelling, identification, estimation and signal processing. The book covers such topics as subspace methods, stochastic realization, state space modelling, and identification and parameter estimation.

"Modeling, Identification, and Estimation Stochastic Realization and System Identification, Giorgio Picci General State Space Modeling, Will Gersch and Genshiro Kitagawa Canonical Variate Analysis in Control and Signal Processing, Wallace E. Larimore Models in Generalized MA Form for Identification of Continuous-Time Systems, Ganti Prasada Rao and A. V. B. Subrahmanyam Multiresolution Approach to Identification of System Impulse Response, Zi-Jiang Yang, Setsuo Sagara, and Teruo Tsuji Comparative Study of Rank Test Methods for ARMA Order Estimation, Joakim Sorelius, Torsten Söderström, Petre Stoica, and Mats Cedervall A MAP Recursive Nonlinear Filtering, Shin Ichi Aihara and Arunabha Bagchi Stochastic Properties of the H* Filter, Kiyotsugu Takaba and Tohru Katayama Reduced Order Functional Estimator for Linear Stochastic Systems, Takayoshi Nakamizo Shares in Emergent Markets: Dynamics and Statistical Properties of Equilibrium Classification of Agents in Evolutionary Models, Masanao Aoki Fuzzy Random Data Obtained as Vague Perceptions of Random Phenomena, Tokuo Fukuda Signal Processing Theory of Cyclostationary Processes and Its Applications, Hideaki Sakai and Shuichi Ohno Stochastic System Identification Using Polyspectra, Jitendra K. Tugnait Blind Deconvolution of Multichannel Linear Time-Invariant Systems of Nonminimum Phase, Yujiro Inouye Bayesian Approaches for Robust Array Signal Processing, A. Lee Swindlehurst and Mats Viberg Selected Stochastic Methods and Signal Processing Used in Radar Systems, T. Sen Lee Statistical Methods for Robust Change Detection in Dynamical Systems with Model Uncertainty, Kousuke Kumamaru, Jinglu Hu, Katsuhiro Inoue, and Torsten Söderström Detecting Changes in Acting Stochastic Models and Model Implementation via Stochastic Binary Neural Networks, Anthony Burrell, Achilles G. Kogiantis, and P. Papantoni-Kazakos Invariant Features Associated with a Conditional Distribution Induced by Self-Similar Patterns, Kohji Kamejima Gibbs Random Image Models and Sampling, Masaki Suwa and Sueo Sugimoto "