Sökning: "Minimum mean-square error"
Visar resultat 1 - 5 av 16 avhandlingar innehållade orden Minimum mean-square error.
1. Linear Models of Nonlinear Systems
Sammanfattning : Linear time-invariant approximations of nonlinear systems are used in many applications and can be obtained in several ways. For example, using system identification and the prediction-error method, it is always possible to estimate a linear model without considering the fact that the input and output measurements in many cases come from a nonlinear system. LÄS MER
2. Maximum a posteriori deconvulution of ultrasonic data with applications in nondestructive testing : Multiple transducer and robustness is
Sammanfattning : In the thesis, various aspects of deconvolution of ultrasonic pulse-echo signals in nondestructive testing are treated. The deconvolution problem is formulated as estimation of a reflection sequence which is the impulse characteristic of the inspected object and the estimation is performed using either maximum a posteriori (MAP) or linear minimum mean square error (MMSE) estimators. LÄS MER
3. Some Results on Linear Models of Nonlinear Systems
Sammanfattning : Linear time-invariant approximations of nonlinear systems are used in many a pplications. Such approximations can be obtained in many ways. LÄS MER
4. Robust Transmit Signal Design and Channel Estimation for Multiantenna Systems
Sammanfattning : In the development of advanced signal processing techniques, dealing with both uncertainties and computational burden is essential. Taking the uncertainties into consideration is required in order to guarantee a certain level of performance, even when the system is designed based on imperfect prior knowledge. LÄS MER
5. System identification with input uncertainties : an EM kernel-based approach
Sammanfattning : Many classical problems in system identification, such as the classical predictionerror method and regularized system identification, identification of Hammersteinand cascaded systems, blind system identification, as well as errors-in-variablesproblems and estimation with missing data, can be seen as particular instancesof the general problem of the identification of systems with limited information.In this thesis, we introduce a framework for the identification of linear dynamicalsystems subject to inputs that are not perfectly known. LÄS MER