A inteligibilidade da palavra em igrejas católicas, através de análises de carácter objectivo e subjectivo
Lencastre, Margarida Maria Mendes de Freitas de Queiroz e
1988-01-01
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In radio, radar, sonar, and seismic signal detection there is often the problem of processing received signals which have been distorted by a linear operation in the process of being transmitted. Examples are scattering and multiple-path propagation of radio waves. Usually the nature of this linear operation cannot be known very precisely in advance, and it often is changing in time, so that in order to carry out effective processing of the received signals it is necessary repeatedly to test and measure the mode of transmission, or channel as it will be called.In this paper the beginnings of a theory are established concerning time-varying and random linear channels with the intent of characterizing classes of channels which can be determined exactly or approximately by measurement, showing how the measurements can be made, analyzing t...
The notion of system trajectory of a time-varying input-output, dynamical system is reviewed. By introducing a probability measure on a class of such systems a stochastic system, the randomized system, is defined. The randomized system has a trajectory induced by the trajectories of the original systems. A theorem is proved giving fairly general conditions under which the randomized system trajectory is generated by a strongly continuous semigroup of bounded linear operators in a Banach space. An example is presented for a system represented by a quadratic integral operator.
Cylindrical Wiener processes in real separable Banach spaces are defined, and an approximation theorem involving scalar Wiener processes is given for such processes. A weak stochastic integral for Banach spaces involving a cylindrical Wiener process as integrator and an operator-valued stochastic process as integrand is defined. Basic properties of this integral are stated and proved.
A system is conceived of as being slowly varying if it changes slowly enough to permit identification to within a specified error. A generic model is developed to study the identifiability and identification of slowly varying systems. The model is suitable for a large variety of nonlinear, time-varying, causal, bounded memory systems; it has finitely many parameters and is linear in its parameters. Results are obtained with the use of this general model that give guaranteed accuracy of identification as a function of the prior knowledge of the unknown system, the maximum rate of time variation of the system, and the characteristics of output observation noise. To derive these results, a recursive estimation procedure is developed for time-discrete linear dynamical system structures in which the observation noise is statistical but the ...


