Quasi-Optimal Filtering in Inverse Problems

A way of constructing a nonlinear filter close to the optimal Kolmogorov - Wiener filter is proposed within the framework of the statistical approach to inverse problems. Quasi-optimal filtering, which has no Bayesian assumptions, produces stable and efficient solutions by relying solely on the internal resources of the inverse theory. The exact representation is given of the Feasible Region for inverse solutions that follows from the statistical consideration.Comment: 9 pages, 240 K

Notch Filtering Suitable for Real Time Removal of Power Line Interference

This paper presents a high performance notch filtering for real time suppression of power line interference in a general signal. The disturbing signal is suppressed using an optimal notch FIR filter with tunable notch frequency. The tuning of the filter preserves its selectivity, most importantly the specified attenuation at the notch frequency. One example and two Matlab functions demonstrate the performance, robustness and usefulness of the proposed procedure for the design and tuning of optimal notch FIR filters suitable in the real time notch filtering

Continuous Non-Demolition Observation, Quantum Filtering and Optimal Estimation

A quantum stochastic model for an open dynamical system (quantum receiver) and output multi-channel of observation with an additive nonvacuum quantum noise is given. A quantum stochastic Master equation for the corresponding instrument is derived and quantum stochastic filtering equations both for the Heisenberg operators and the reduced density matrix of the system under the nondemolition observation are found. Thus the dynamical problem of quantum filtering is generalized for a noncommutative output process, and a quantum stochastic model and optimal filtering equation for the dynamical estimation of an input Markovian process is found. The results are illustrated on an example of optimal estimation of an input Gaussian diffusion signal, an unknown gravitational force say in a quantum optical or Weber's antenna for detection and filtering a gravitational waves.Comment: A revised version of the paper published in the Proceedings of the 1st QCMC conference, Paris 199

Geomagnetic modeling by optimal recursive filtering

The results of a preliminary study to determine the feasibility of using Kalman filter techniques for geomagnetic field modeling are given. Specifically, five separate field models were computed using observatory annual means, satellite, survey and airborne data for the years 1950 to 1976. Each of the individual field models used approximately five years of data. These five models were combined using a recursive information filter (a Kalman filter written in terms of information matrices rather than covariance matrices.) The resulting estimate of the geomagnetic field and its secular variation was propogated four years past the data to the time of the MAGSAT data. The accuracy with which this field model matched the MAGSAT data was evaluated by comparisons with predictions from other pre-MAGSAT field models. The field estimate obtained by recursive estimation was found to be superior to all other models