by Karl J. Astrom
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by Brian D. O. Anderson
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by Andrew H. Jazwinski
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by Thomas M. Cover
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Time Series Analysis: Forecasting and Control (Wiley Series in Probability and Statistics) by George E. P. Box |
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Product Description
This text provides an introduction to the field of stochastic dynamic systems, their estimation and control. Including the provision of computer derivations of key results, the book covers both state-space methods and methods based on the polynomial approach, with similarities and differences between the two highlighted. Some nonlinear aspects (including the bispectrum and extended Kalman filter) are also introduced and analyzed. Processes with complex-valued data are treated wherever convenient as this is of interest in many signal processing and communication problems.
From the Back Cover
The aim of this text is to give a comprehensive introduction to the field of stochastic dynamic systems, their estimation and control, including the provision of complete derivations of key results. The book covers both state-space methods and methods based on the polynomial approach, with similarities and differences between the two highlighted. Some nonlinear aspects (including the bispectrum and extended Kalman filter) are also introduced and analyzed. Processes with complex-valued data are treated wherever convenient as this is of interest in many signal and communication problems.
This text provides an introduction to the field of stochastic dynamic systems, their estimation and control. Including the provision of computer derivations of key results, the book covers both state-space methods and methods based on the polynomial approach, with similarities and differences between the two highlighted. Some nonlinear aspects (including the bispectrum and extended Kalman filter) are also introduced and analyzed. Processes with complex-valued data are treated wherever convenient as this is of interest in many signal processing and communication problems.
From the Back Cover
The aim of this text is to give a comprehensive introduction to the field of stochastic dynamic systems, their estimation and control, including the provision of complete derivations of key results. The book covers both state-space methods and methods based on the polynomial approach, with similarities and differences between the two highlighted. Some nonlinear aspects (including the bispectrum and extended Kalman filter) are also introduced and analyzed. Processes with complex-valued data are treated wherever convenient as this is of interest in many signal and communication problems.
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