Time-domain Filtering and Control with Empirical Data
نویسنده
چکیده
The transmission matrix, introduced by Friedland in 1957, can be used to characterize a linear, time invariant system having an emprically-determined impulse response. The Wiener-Kalman filter can be determined by Cholesky factorization of a covariance matrix formed from the transmission matrix. An analogous result is given for linear, quadratic control. The method is illustrated by several examples.
منابع مشابه
Application of Single-Frequency Time-Space Filtering Technique for Seismic Ground Roll and Random Noise Attenuation
Time-frequency filtering is an acceptable technique for attenuating noise in 2-D (time-space) and 3-D (time-space-space) reflection seismic data. The common approach for this purpose is transforming each seismic signal from 1-D time domain to a 2-D time-frequency domain and then denoising the signal by a designed filter and finally transforming back the filtered signal to original time domain. ...
متن کاملDelay Spoofing Reduction in GPS Navigation System based on Time and Transform Domain Adaptive Filtering
Due to widespread use of Global Positioning System (GPS) in different applications, the issue of GPS signal interference cancelation is becoming an increasing concern. One of the most important intentional interferences is spoofing signals. An effective interference (delay spoof) reduction method based on adaptive filtering is developed in this paper. The principle of method is using adaptive f...
متن کاملEmpirical Mode Decomposition based Adaptive Filtering for Orthogonal Frequency Division Multiplexing Channel Estimation
This paper presents an empirical mode decomposition (EMD) based adaptive filter (AF) for channel estimation in OFDM system. In this method, length of channel impulse response (CIR) is first approximated using Akaike information criterion (AIC). Then, CIR is estimated using adaptive filter with EMD decomposed IMF of the received OFDM symbol. The correlation and kurtosis measures are used to sel...
متن کاملRobust state estimation in power systems using pre-filtering measurement data
State estimation is the foundation of any control and decision making in power networks. The first requirement for a secure network is a precise and safe state estimator in order to make decisions based on accurate knowledge of the network status. This paper introduces a new estimator which is able to detect bad data with few calculations without need for repetitions and estimation residual cal...
متن کاملOptimized computational Afin image algorithm using combination of update coefficients and wavelet packet conversion
Updating Optimal Coefficients and Selected Observations Affine Projection is an effective way to reduce the computational and power consumption of this algorithm in the application of adaptive filters. On the other hand, the calculation of this algorithm can be reduced by using subbands and applying the concept of filtering the Set-Membership in each subband. Considering these concepts, the fir...
متن کامل